WWW21-Information_Extraction_from_Co-Occurring_Similar_Entities.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Information Extraction from Similar Co-Occurring Entities\n",
    "*TODO: Adapt this notebook to the refactored extraction code of CaLiGraph*\n",
    "\n",
    "This notebook contains the necessary code for reproducing the results of the paper \"Information Extraction from Similar Co-Occurring Entities\". The functionality for extracting new entities and facts for CaLiGraph is already implemented in the extraction framework. Here, we simply run this functionality to show the results and extend some parts to extract results for DBpedia as well.\n",
    "\n",
    "To reproduce the results, parts of the CaLiGraph extraction framework need to be run first. If necessary, the extraction will be triggered automatically from this notebook. A full run of this notebook needs roughly two days (plus three additional days when running the extraction framework). For hardware requirements, refer to the README.\n",
    "\n",
    "Evaluation results of the paper and all triples produced in this notebook can be downloaded [here](http://data.dws.informatik.uni-mannheim.de/CaLiGraph/www2021/).\n",
    "\n",
    "*Note: The results produced here differ slightly from the results of the paper as we use new Wikipedia and DBpedia dumps from 2020 instead of from 2016.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preparations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-03-03 16:50:32,375 DEBUG: RDFLib Version: 5.0.0\n"
     ]
    }
   ],
   "source": [
    "# imports\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "pd.options.display.max_rows = 50\n",
    "pd.options.display.max_columns = 50\n",
    "pd.options.display.max_colwidth = 100\n",
    "\n",
    "import impl.dbpedia.store as dbp_store\n",
    "import impl.dbpedia.util as dbp_util\n",
    "import impl.util.rdf as rdf_util\n",
    "import impl.util.serialize as serialize_util\n",
    "from impl import caligraph\n",
    "import impl.caligraph.util as clg_util\n",
    "from impl.listing import context, extract"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-03-03 20:15:32,126 INFO: Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n",
      "2021-03-03 20:15:32,130 INFO: NumExpr defaulting to 8 threads.\n"
     ]
    }
   ],
   "source": [
    "# load data\n",
    "graph = caligraph.get_axiom_graph()\n",
    "df = context.retrieve_page_entity_context(graph)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Type Extraction for *DBpedia*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute valid combinations of types and NE tags\n",
    "\n",
    "def _get_transitive_types_dbp(entity_name: str) -> set:\n",
    "    dbp_uri = dbp_util.name2resource(str(entity_name))\n",
    "    transitive_types = dbp_store.get_transitive_types(dbp_uri).difference({rdf_util.CLASS_OWL_THING})\n",
    "    return {dbp_util.type2name(t) for t in transitive_types}\n",
    "\n",
    "def _get_valid_tags_for_entity_types_dbp(dft: pd.DataFrame, threshold: float) -> dict:\n",
    "    tag_probabilities = context._get_tag_probabilities(dft)\n",
    "    valid_tags = tag_probabilities[tag_probabilities['tag_fit'] >= threshold].groupby('E_enttype')['E_tag'].apply(lambda x: x.values.tolist()).to_dict()\n",
    "    for ent_type in set(valid_tags):  # assign tags of parents to types without tags (to avoid inconsistencies)\n",
    "        valid_tags[ent_type] = _compute_valid_tags_for_type_dbp(ent_type, valid_tags)\n",
    "    return valid_tags\n",
    "\n",
    "def _compute_valid_tags_for_type_dbp(ent_type: str, valid_tags: dict) -> set:\n",
    "    if ent_type not in valid_tags:\n",
    "        return set()\n",
    "    if not valid_tags[ent_type]:\n",
    "        valid_tags[ent_type] = {tag for ptype in _get_supertypes_dbp(ent_type) for tag in _compute_valid_tags_for_type_dbp(ptype, valid_tags)}\n",
    "    return valid_tags[ent_type]\n",
    "\n",
    "def _get_supertypes_dbp(type_name: str) -> set:\n",
    "    dbp_type = dbp_util.name2type(str(type_name))\n",
    "    return {dbp_util.type2name(t) for t in dbp_store.get_supertypes(dbp_type).difference({rdf_util.CLASS_OWL_THING})}\n",
    "\n",
    "df_types_dbp = pd.DataFrame([{'E_ent': ent, 'E_enttype': t} for ent in df['E_ent'].unique() for t in _get_transitive_types_dbp(ent)])\n",
    "dft_dbp = pd.merge(left=df, right=df_types_dbp, on='E_ent')\n",
    "valid_tags_dbp = _get_valid_tags_for_entity_types_dbp(dft_dbp, .35)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract rules\n",
    "\n",
    "rule_dfs_dbp = {}\n",
    "for rule_name, rule_pattern in extract.RULE_PATTERNS.items():\n",
    "    dft_by_page = extract._aggregate_types_by_page(dft_dbp, rule_pattern)\n",
    "    rule_dfs_dbp[rule_name] = extract._aggregate_types_by_section(dft_by_page, rule_pattern)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Threshold Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract all possible new types up to a very low threshold (mean >= 0.25 and std <= 0.75)\n",
    "\n",
    "threshold_rule_dfs_dbp = [rule_dfs_dbp[rule_name].query(f'micro_mean > .25 & micro_std < .75').reset_index()[rule_pattern + ['E_enttype', 'micro_mean', 'micro_std']].drop_duplicates() for rule_name, rule_pattern in extract.RULE_PATTERNS.items()]\n",
    "threshold_types_dbp = extract._extract_new_types(threshold_rule_dfs_dbp, df, df_types_dbp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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2besdsxK6iNTNsGEwaVKokZuF50mT6tXLpUOHDnz99dcbp7/88ku23XZbWrVqxbRp01gY/SI48MADeeKJJ1i9ejUrV66scy+U1O3F7brrrlVq0UcddRS33HLLxkRc0eRSUlLCjBkzgNDmXhcffvghvXv3rtN745TQRaTuhg2DsjLYsCE81yOZA3Tu3JkDDzyQ3r17c9FFFzFs2DCmT59Onz59uPvuu9l9990BGDBgAIMGDaJv374cffTR9OnTh6222qrW2+vbty8tWrRgr7322uSk6JZbbkmPHj2YN28eAMOHD6eoqIi+ffuy1157bewd8/vf/54xY8ZQWlpKixYtah3D559/Ttu2bdluu+1q/d5UebtJdGlpqSf5jkXqhy7N0dy5c9ljjz3yHUZWVq5cSfv27Vm1ahWHHHIIkyZNon///jndxqOPPsqMGTO44oorcrreuOuvv56OHTty+umnb7Is3edhZjPcvTTdunRSVESapZEjRzJnzhxWr17NKaeckvNkDnD88cezrB69drKx9dZbc9JJJ+VkXUroItIspbsg6Oyzz+aVV16pMm/MmDGcdtppdd7O8OHD6/zebNQntlRK6CKSGBMnTsx3CHmlk6IiIgmhhC4ikhBK6CIiCaE2dBHJKBfdb+PUFbdhqYYuIk1GQwyf+/7779OvXz/23ntv5s+fz/e+9z2g5qFzmyMldBFpMhoiodd1LPTmSAldRJqM+Hjo5513Xl7HQm+O1IYuIk1GfDz09evXs2rVqryMhd5cKaGLSJOUz7HQmysldBFpkuJjobdq1YqSkpJGGwu9uVJCF5GMGrubYXx88urGQj/jjDO45JJLWL9+PU8++SQjR46s17aSQgldRJqM+HjoAwYM4P3336dPnz6UlpamHQu9a9euORkL/dRTT+W8887L9e40uqwSupkNBG4AWgC3ufuVacr8FBgPODDL3X+ewzhFZDORTVfCCy+8kPHjx28cC726e3GOHz++yvTKlSsBaNWqFc8//3y9Ym1qakzoZtYCmAgcBZQDb5rZFHefEyvTE7gEONDdl5vZtg0VsIhIY4yF3hxlU0PfF5jn7gsAzOw+YDAwJ1ZmBDDR3ZcDuPt/ch2oiEiFxhoLvbnJJqHvCHwamy4H9kspsyuAmb1CaJYZ7+5Pp67IzEYCIwGKiorqEq+INDB333h3+uYkaWOh1+X2oLk6KdoS6AkcBnQDXjSzPu6+Il7I3ScBkyDcUzRH286J+g5CpEGHJAnatGnDsmXL6Ny5c7NM6knh7ixbtow2bdrU6n3ZJPRFwE6x6W7RvLhy4A13Xwd8bGYfEhL8m7WKRkTyqlu3bpSXl7NkyZJ8h7LZa9OmDd26davVe7JJ6G8CPc2sOyGRDwFSe7A8BgwF/mpmXQhNMAtqFYmI5F2rVq3o3r17vsOQOqpxcC53Xw+MBp4B5gIPuPtsM7vMzAZFxZ4BlpnZHGAacJG7N+ytskVEpIqsRlt096nuvqu793D3CdG8S919SvTa3f18d+/l7n3c/b6GDDrpBs2exst/OQ0KCqCkBCZPzndIItIMaPjcJmbQ7Glc+fSNdPtqCbjDwoUwcmT9kvrkyeGLQV8QIommS/+bmItfvJt269dUnblqFYwbB8OGwd13w2efQevW4dGmDWy3HQwcGMq++SasWRPmt24N//gH/O538O23YXnFFwSE9YlIYiihNwXuEHUR2/GrDL0LPvkkPP/lL/D661WX7bdfZUI//XR4993qt7dqVSj3zDPQrRvsvz8Mik6HLFkC22wDLVpUv47Jk8OXzCefQFERTJigLwiRPFNCzxPzDfRf9D7HvP8yP/joNY4/6TqWtO/E0nZbUbjqy03fUHEh1ksvhRr4mjWwenV4jiffO+6A5csry5x4YvoA1qyBF1+ERYtCIh40KHyxFBfDunWw/fYh2e+4I5xwAgwdGpa//DJMnw6//W34YgDV+kWaCCX0RrbdV0sZ+a9HOPqDV9h+5TLWtGjFP3feh/ZrV7GETlz+/eFc+fSNVZtd2rULNWCAli3DY8st02+gtLTqdHFxSLipiouhrAw2bAhfDADffQfXXhuSfHl5eH7vPejXLyz/4gs45JD02121Ci65BLbeGrp3D+vPFKOINAgl9AZWURNfX9CCWTvsBsDPZz3Ni9378/92P43ne+zLytbtNpafsme47+HFL95Nt6+X1r85Y8KEUHuuqE1D1S+IgoIwDeGL4qyzMq9ryy1DM81//Vf65eXl8KMfVU5vu204CXvFFXDUUbB0Kbz1VphXXBza+OPUjCNSL0ro9TRo9jQufvFuuDqWfIcOZZ/yORzz/ssba+L/6Lk/I0/4LZ917EK/c+9hdavMl/RO2fNwpux5+CbDCdRteIKtGfT9M3PzBdGmDfzgB5lr/d26wf33h5r/xx9XPldcvvzaa5Vt9Wawww6hNv/nP8Ps2TBihE7eitSD1WUAmFwoLS316dOn52Xb6dQlWVZ0MdykeaRHD3j33Y3NKU/tdiDP7bJflZp4NnKT0DOvr84mT05f6580qfrk++WX8M47VZN9WRncckv4oqiuaUhEADCzGe5emm7Z5ldDr+PP+jbrVrO2RSs2FLRg1yVlHPDJu1zw4v+m72K4eDFjfnRBnZJ4s1BxvGp7HLfaCg4+ODxSVfTiSbVwYWjbr6nXjYhsZgk9tWa5cGH4mV9ezoFl63mvaw++bNuB/uVzOfWtJyj8ZjnbrlxO4cov6Lh2FUf9ciIfFRaz/yfv8t/P3kLG3zbLlvF41BaeWMOG5bYppKgofQ29ffvKZP63v8Hhh4eeNyKyic3rStFx46o2E0Bosx07lsn3/5a+n30EwFZrVtJ38Ue02PAdcwtLeLjPEVx9yMmsaNsBgEd7f599Rv+NRR0L029HY73X3oQJlSdnK7RrBzffHF5//jmcckpogjnhhHDB1IYNjR+nSBPWLGvodW1LXrDwk/TfYGb8bMgfmLttGGVuWo8BTOsxION6vm69JbSGqw85OXMXwxqu7ZEUNTXjdO0KH34Y2un/+ld49FHYeefwq2v//fMXt0gTslnV0P/dsUv6BUVFvFHUh6/atK/V+qbseThjB46mvGNh6LVRXFzziUHJbNiwyr7xZWWbHscePeCqq+DTT+Hee0MPmZ13DstefhleeCFc/CSymdqsEvrVh5zMqpYpfZ/jfbLrYMqeh3PQmX/NnIQk91q3hiFD4NlnQ193gCuvDO3re+wB118fLoLSoGSymdmsErpq1An24INw553QqROcf35I9KedFk605mrUSpEmbrNK6KAadWK1bRtOmr72GsycGabXratapmLUSpGE2uwSumwG9toLvvkm/bJM/d1FEkAJXZIpU9fRgoLQ5VEkgZTQJZnS9Wtv3RoKC8PgYuPH5yUskYakhC7JNGxYOOFdXFx5Avz228P4Mb/7Hfzwh6HcmjXq6iiJ0SwvLBLJSqbhCS67rPL1mDEwf364IrVHj8aLTaQBZJXQzWwgcAPQArjN3a9MWX4qcA2wKJp1o7vflsM4pYE0mREc86Vfv3CRUp8+oRnmvPOgVat8RyVSJzUmdDNrAUwEjgLKgTfNbIq7z0kper+7j26AGKUZqe8XBDTyl8SoUXDssXDOOfDrX8M994S+6nvu2XgxiORINm3o+wLz3H2Bu68F7gMGN2xYIo1oxx3hkUfCY9Uq3TpPmq1sEvqOwKex6fJoXqofm9k7ZvaQme2UbkVmNtLMppvZ9CVLMtzdXiRfjj8e3n8/DBPgDsOHw9Sp+Y5KJGu56uXyBFDi7n2B/wPuSlfI3Se5e6m7lxYWZhh6ViSfCqJ/iWXL4NVX4ZhjYOjQMHyvSBOXTUJfBMRr3N2oPPkJgLsvc/eKMWRvA/bJTXgiedKlC7z9Nvz3f4emmD32gDvu0IBf0qRlk9DfBHqaWXcz2wIYAkyJFzCz7WOTg4C5uQtRJE9at4ZLL4VZs6B37zDo14gRGvBLmqwaE7q7rwdGA88QEvUD7j7bzC4zs+gW7pxrZrPNbBZwLnBqQwUs0uh23z2Mtb7lluEOV3Ea8EuakKz6obv7VGBqyrxLY68vAS7JbWgiTUhBASxenH6ZBvySJkKX/otkq7p7xV5xBaxd23ixiKShhC6SrXQDfrVpA3vvDY8/XnmFqW5eLXmihC6SrXQDft12G8yYEdrYzUJ3x912C7fBS21vF2lgSugitZHpRtYVV5euWBES/fnnwy67wMSJYURHkUaghC6SSz16hJtXv/BCeD16NOy6K3z5Zb4jk82AErpIQzj0UPjnP8PdkU46CbbaKsx/6SVYvz6/sUliKaGLNBQzOOqo0AMGYMECOOww6NUrXIz03Xe68lRySgldpLF07w4PPwxt28IvfhG6Qf7yl7ryVHJGCV2ksZjBcceFMWIeeAD+859N+67rylOpByV0kcZWUAA/+Ulockln4UKYN69xY5JEUEIXyZfqrjzt2TP0Z7/jjsaLR5o9JXSRfEl35Wm7dnDddfCnP8HOO4dmGoB//zvcgOPWW6G8vPFjlWZBCV0kX9JdeTppUrhR9TnnwN//DqedFsp+/DG89VY4abrTTuHm1r/5TfoBw9RzZrOV1WiLItJAhg2rvNq0OgceGK5MnTMHnnoq3Brvmmvg7LPD8ueeC7X4b76BCy4IJ1ehsudMxbYk0VRDF2kuzGDPPeHii8OVqF98EW5wDXDnnXDyyXDmmZXJvMKqVfDrX4eEv3Jl6CJZGw1R428O62wOMaZQDV2kuerQofL1XXfBmDEwYED6sosWVSb/Fi2gY0f4wQ/gvvvCvDPOCMm+Y8fw2Gor6NMHvvoq1PDjNf7hw8PzSSeF5h+A994Lz2aVj222ga5dw7g38+dXLn/iidA1s2LwsoULw52gli4N3TorbL11iGPduvRNS506hWOwdi3cckv40kpdJ8CJJ0K6m9J37hyuCVi9OgyqFvfoo2F98f0eMQKWL4cTTgjzunSBLbYIv4rSDe1QWBhG4Fy5MhzHRx4JX8bxGHP860kJXSQJCgqgtDS0wy9cuOnywkK4/PKQeL76Kjz36FG5vKwsJN2KZWvXws9+Bq+/vmmNf/XqkJAXLAijTQL07btpzf9Xv6ocdXLXXauP/9tvQ/lf/apy3lVXhQS4cGHo9ZPqppvCL5LZs+Hcc9Ovc9y40JvokEM2Xf7YYzB4MDz/fLgZeE2+/Tac2zjnnDD9xhuw775w772VXx5xc+aEe9HeemsYrC2diusOlNBFZBMTJlStUUPoOXP99dUnjWeeqTq9Zk2oGXfsmL68GZx1VuX0Aw+EhB5/VCTx1q3hb3+rnH/yyZnjiHfTLC0Nz9tuC7ffvmnZAw4IzzvttOmyCp98Er4Mbr1102V77RWee/cOJ6PjKmrO6dxyS3guKQnPBx1UOS9uu+3C8xFHhOVnnJE5xhxRQhdJkoqkPW5cSBRFRSHJ17YG2Lp1eBQVpa/xFxVB//6V0yeemHldLVtW3f7vfpd+ncXFlb164jp2DEMkZNKlS+ZfJkVFIbEOH575/UVFm9awJ0zIHGNqst999/DIpG/f8PjDHzLHmCM6KSqSNJnGbK+LTH3lJ0xI9jqbQ4xpKKGLSGaZ+srX50uiOayzOcSYRlZNLmY2ELgBaAHc5u5XZij3Y+AhYIC7T89ZlCKSP9n2lU/aOptDjClqrKGbWQtgInA00AsYama90pTrAIwB3sh1kCIiUrNsmlz2Bea5+wJ3XwvcBwxOU+5y4CpgdQ7jExGRLGWT0HcEPo1Nl0fzNjKz/sBO7v5UdSsys5FmNt3Mpi9J19FfRETqrN4nRc2sALgOuKCmsu4+yd1L3b20sLCwvpsWEZGYbBL6IiDec79bNK9CB6A38IKZlQH7A1PMrDRXQYqISM2ySehvAj3NrLuZbQEMAaZULHT3L929i7uXuHsJ8DowSL1cREQaV40J3d3XA6OBZ4C5wAPuPtvMLjOzQQ0doIiIZCerfujuPhWYmjLv0gxlD6t/WCIiUlu6UlREJCE0OJc0eSVjq+0NW6OyK7MYGlUkAVRDFxFJCCV0EZGEUEIXEUkIJXQRkYRQQhcRSQgldBGRhFBCFxFJCCV0EZGEUEIXEUkIJXQRkYRQQhcRSQgldBGRhFBCFxFJCCV0EZGEUEIXEUkIJXQRkYRQQhcRSQgldBGRhFBCFxFJiKwSupkNNLMPzGyemY1Ns3yUmb1rZjPN7GUz65X7UEVEpDo1JnQzawFMBI4GegFD0yTse9y9j7v3A64Grst1oCIiUr1sauj7AvPcfYG7rwXuAwbHC7j7V7HJLQHPXYgiIpKNllmU2RH4NDZdDuyXWsjMzgbOB7YAvp9uRWY2EhgJUFRUVNtYRUSkGjk7KeruE929B/Br4LcZykxy91J3Ly0sLMzVpkVEhOwS+iJgp9h0t2heJvcBx9UjJhERqYNsmlzeBHqaWXdCIh8C/DxewMx6uvtH0eQxwEeISOKVjH2qXu8vu/KYHEUikEVCd/f1ZjYaeAZoAdzh7rPN7DJgurtPAUab2ZHAOmA5cEpDBi0iIpvKpoaOu08FpqbMuzT2ekyO4xJpMPWtVYJqls3J5vQrQleKiogkhBK6iEhCKKGLiCSEErqISEIooYuIJERWvVxEpPnbnHp7bK6U0EVyINfJcnPtWrm57neuqMlFRCQhlNBFRBJCCV1EJCGU0EVEEkIJXUQkIZTQRUQSQgldRCQhlNBFRBJCCV1EJCGU0EVEEkIJXUQkIZTQRUQSQoNziYjUQlMeQEw1dBGRhMgqoZvZQDP7wMzmmdnYNMvPN7M5ZvaOmT1nZsW5D1VERKpTY0I3sxbAROBooBcw1Mx6pRR7Gyh1977AQ8DVuQ5URESql00NfV9gnrsvcPe1wH3A4HgBd5/m7quiydeBbrkNU0REapJNQt8R+DQ2XR7Ny+R04O/pFpjZSDObbmbTlyxZkn2UIiJSo5yeFDWzXwClwDXplrv7JHcvdffSwsLCXG5aRGSzl023xUXATrHpbtG8KszsSGAccKi7r8lNeCIikq1sauhvAj3NrLuZbQEMAabEC5jZ3sAtwCB3/0/uwxQRkZrUmNDdfT0wGngGmAs84O6zzewyMxsUFbsGaA88aGYzzWxKhtWJiEgDyepKUXefCkxNmXdp7PWROY5LRERqSVeKiogkhBK6iEhCKKGLiCSEErqISEIooYuIJIQSuohIQiihi4gkhBK6iEhCKKGLiCSEErqISEIooYuIJIQSuohIQiihi4gkhBK6iEhCKKGLiCSEErqISEIooYuIJIQSuohIQiihi4gkhBK6iEhCKKGLiCREVgndzAaa2QdmNs/MxqZZfoiZvWVm683sxNyHKSIiNakxoZtZC2AicDTQCxhqZr1Sin0CnArck+sARUQkOy2zKLMvMM/dFwCY2X3AYGBORQF3L4uWbWiAGEVEJAvZNLnsCHwamy6P5tWamY00s+lmNn3JkiV1WYWIiGTQqCdF3X2Su5e6e2lhYWFjblpEJPGySeiLgJ1i092ieSIi0oRkk9DfBHqaWXcz2wIYAkxp2LBERKS2akzo7r4eGA08A8wFHnD32WZ2mZkNAjCzAWZWDvwEuMXMZjdk0CIisqlserng7lOBqSnzLo29fpPQFCMiInmiK0VFRBJCCV1EJCGU0EVEEkIJXUQkIZTQRUQSQgldRCQhlNBFRBJCCV1EJCGU0EVEEkIJXUQkIZTQRUQSQgldRCQhlNBFRBJCCV1EJCGU0EVEEkIJXUQkIZTQRUQSQgldRCQhlNBFRBJCCV1EJCGU0EVEEiKrhG5mA83sAzObZ2Zj0yxvbWb3R8vfMLOSnEcqIiLVqjGhm1kLYCJwNNALGGpmvVKKnQ4sd/ddgOuBq3IdqIiIVC+bGvq+wDx3X+Dua4H7gMEpZQYDd0WvHwKOMDPLXZgiIlITc/fqC5idCAx09+HR9EnAfu4+OlbmvahMeTQ9PyqzNGVdI4GR0eRuwAdZxtkFWFpjqfxSjLnTHOJUjLmhGGuv2N0L0y1o2ZhRuPskYFJt32dm0929tAFCyhnFmDvNIU7FmBuKMbeyaXJZBOwUm+4WzUtbxsxaAlsBy3IRoIiIZCebhP4m0NPMupvZFsAQYEpKmSnAKdHrE4Hnvaa2HBERyakam1zcfb2ZjQaeAVoAd7j7bDO7DJju7lOA24H/NbN5wBeEpJ9LtW6myQPFmDvNIU7FmBuKMYdqPCkqIiLNg64UFRFJCCV0EZGEaFIJvTkMMZBFjIeY2Vtmtj7qw9/osojxfDObY2bvmNlzZlbcBGMcZWbvmtlMM3s5zdXJeY8xVu7HZuZmlpeubVkcy1PNbEl0LGea2fCmFmNU5qfR3+VsM7unqcVoZtfHjuGHZraisWOskbs3iQfhhOt8YGdgC2AW0CulzFnAzdHrIcD9TTDGEqAvcDdwYhM9jocD7aLXZzbR49gx9noQ8HRTizEq1wF4EXgdKG2in/epwI2NHVstY+wJvA10iqa3bWoxppQ/h9BBJC/HNNOjKdXQm8MQAzXG6O5l7v4OsKER44rLJsZp7r4qmnydcG1BU4vxq9jklkBjn73P5u8R4HLC2EWrGzO4mGzjzKdsYhwBTHT35QDu/p8mGGPcUODeRomsFppSQt8R+DQ2XR7NS1vG3dcDXwKdGyW6lO1H0sWYb7WN8XTg7w0a0aayitHMzo6GkbgaOLeRYqtQY4xm1h/Yyd2faszAUmT7ef84amJ7yMx2SrO8IWUT467Armb2ipm9bmYDGy26IOv/m6iJsjvwfCPEVStNKaFLIzOzXwClwDX5jiUdd5/o7j2AXwO/zXc8cWZWAFwHXJDvWLLwBFDi7n2B/6PyV25T0pLQ7HIYofZ7q5ltnc+AqjEEeMjdv8t3IKmaUkJvDkMMZBNjvmUVo5kdCYwDBrn7mkaKrUJtj+N9wHENGVAaNcXYAegNvGBmZcD+wJQ8nBit8Vi6+7LYZ3wbsE8jxVYhm8+7HJji7uvc/WPgQ0KCbyy1+ZscQhNsbgGa1EnRlsACwk+ZipMSe6aUOZuqJ0UfaGoxxsreSX5OimZzHPcmnADq2YQ/656x18cSrkpuUjGmlH+B/JwUzeZYbh97fTzwehOMcSBwV/S6C6H5o3NTijEqtztQRnRRZlN75D2AlIP1Q8I383xgXDTvMkItEqAN8CAwD/gXsHMTjHEAobbxDeHXw+wmGOOzwOfAzOgxpQnGeAMwO4pvWnXJNF8xppTNS0LP8lj+v+hYzoqO5e5NMEYjNGHNAd4FhjS1GKPp8cCV+fics3no0n8RkYRoSm3oIiJSD0roIiIJoYQuIpIQSugiIgmhhC4ikhBK6JIXZvZdNGrde2b2oJm1q6bsYWb2vdj0cQ05+qKZjYtG/HsninG/aP6vMsUZjWh4Y4bYvzSzt6OR/F40sx81VOyyeVNCl3z51t37uXtvYC0wqpqyhwHfi00fB9QqoUdXFmdT7gDgR0B/D5fKH0nlGB+/AjJ+8VTjJXff2913I4xJc6OZHVGH9YhUSwldmoKXgF3M7NhonPu3zexZM+sajXk/Cjgvqi0fShhO95poukf0eNrMZpjZS2a2O4CZ3WlmN5vZG8DV0fSfzOxVM1uQYbz67YGlHl0q7+5L3f3fZnYusAMwzcymRes/LRoX+1/AgdnsqLvPJFysMjpaR6GZPWxmb0aPA82swMzK4mOZmNlHZta19odWNiv5vrJJj83zAayMnlsCjxPGZe9E5X1uhwP/E70eD1wYe++dxIZVAJ4jGioA2A94PlbuSaBFbPpBQkWmF2G41NS42hOuTv0QuAk4NLasDOgSvd4e+AQoJFwq/gppxhwn/Lp4MmVeP2Bu9Poe4KDodVFs/g3AabF9ejbfn5keTf+R1c9QkQbQ1sxmRq9fAm4HdgPuN7PtCUny45pWYmbtCc0xD8aGxm8dK/KgVx0V7zF33wDMSVfjdfeVZrYPcDDhRiD3m9lYd78zpeh+wAvuviSK437CELDZiI/hfyTQKxZ7x2if7gcuBf5KdDOXLNctmzEldMmXb929X3yGmf0ZuM7dp5jZYYSaeU0KgBWp64r5JmU6PrJk2pujRF8ALxBGUnwXOIVQu8+VvYG50esCYH93r3KDDDN7jdAMVUg4Z3BFDrcvCaU2dGlKtqJyyNJTYvO/JgxXu8m0hzsbfWxmPwGwYK+6BmBmu5lZfNjWfsDCNHG8ARxqZp3NrBXwkyzX3xf4HTAxmvUPwu3MKpb3A3B3Bx4lDFg1190bc5hoaaaU0KUpGU9oOpkBLI3NfwI4PjoJejBhfPSLopOnPYBhwOlmNoswqmB9bsHWHrjLoptoE9rax0fLJgFPm9k0d18czX+N0H5eUePGzAaZ2WWxdR5c0W2RkMjPdffnomXnAqVRF8k5VO3tcz/wi+gZM9vBzKbWY98k4TTaoohIQqiGLiKSEEroIiIJoYQuIpIQSugiIgmhhC4ikhBK6CIiCaGELiKSEP8fv12Su2IZW2kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def visualise_type_thresholds(df, tag_probabilities, bin_count):\n",
    "    \"\"\"Visualize the tag fit in relation to the confidence and consistency (here: std).\"\"\"\n",
    "    df = pd.merge(df, tag_probabilities, on=['E_enttype', 'E_tag'])\n",
    "    \n",
    "    min_mean = .25\n",
    "    mean_conf_labels = [min_mean + x / bin_count * (1 - min_mean) for x in range(bin_count)]\n",
    "    df['mean_confidence'] = pd.cut(df['micro_mean'], bin_count, labels=mean_conf_labels)\n",
    "    \n",
    "    # per bin\n",
    "    plt.bar(x=mean_conf_labels, height=df.groupby('mean_confidence')['tag_fit'].mean().values, width=(1-min_mean)/bin_count*0.8, align='edge', label='tag_fit')\n",
    "    # cumulative\n",
    "    cumulative_tag_fit = [df[df['micro_mean'] > x]['tag_fit'].mean() for x in mean_conf_labels]\n",
    "    plt.plot(mean_conf_labels, cumulative_tag_fit, 'ro--', label='tag_fit (cum)')\n",
    "    plt.xlabel('Pattern Confidence')\n",
    "    plt.title('Pattern Confidence vs. Tagger Confidence')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "    max_std = .75\n",
    "    std_conf_labels = [(x+1) / bin_count * max_std for x in range(bin_count)]\n",
    "    df['std_confidence'] = pd.cut(df['micro_std'], bin_count, labels=std_conf_labels)\n",
    "\n",
    "    # per bin\n",
    "    plt.bar(x=std_conf_labels, height=df.groupby('std_confidence')['tag_fit'].mean().values, width=max_std/bin_count*-0.8, align='edge', label='tag_fit')\n",
    "    # cumulative\n",
    "    cumulative_tag_fit = [df[df['micro_std'] < x]['tag_fit'].mean() for x in std_conf_labels]\n",
    "    plt.plot(std_conf_labels, cumulative_tag_fit, 'ro--', label='tag_fit (cum)')\n",
    "    plt.xlabel('Pattern Std.Dev.')\n",
    "    plt.title('Pattern Std.Dev. vs. Tagger Confidence')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "        \n",
    "visualise_type_thresholds(threshold_types_dbp, context._get_tag_probabilities(dft_dbp), 15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# filter rules by threshold and compute filtered types\n",
    "\n",
    "new_types_dbp = extract._extract_new_types_with_threshold(df, df_types_dbp, rule_dfs_dbp)\n",
    "filtered_types_dbp = extract._filter_new_types_by_tag(new_types_dbp, valid_tags_dbp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>P_basetype</th>\n",
       "      <th>TS_text</th>\n",
       "      <th>E_enttype</th>\n",
       "      <th>micro_mean</th>\n",
       "      <th>micro_std</th>\n",
       "      <th>P</th>\n",
       "      <th>E_ent</th>\n",
       "      <th>E_text</th>\n",
       "      <th>E_tag</th>\n",
       "      <th>TS_ent</th>\n",
       "      <th>S_text</th>\n",
       "      <th>S_ent</th>\n",
       "      <th>E_id</th>\n",
       "      <th>TS_enttype</th>\n",
       "      <th>S_enttype</th>\n",
       "      <th>P_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>29480310</th>\n",
       "      <td>Work</td>\n",
       "      <td>Personnel</td>\n",
       "      <td>Person</td>\n",
       "      <td>0.973151</td>\n",
       "      <td>0.045563</td>\n",
       "      <td>Vanished Gardens</td>\n",
       "      <td>Vanished Gardens--Bernie Grundman</td>\n",
       "      <td>Bernie Grundman</td>\n",
       "      <td>PERSON</td>\n",
       "      <td>None</td>\n",
       "      <td>Personnel</td>\n",
       "      <td>None</td>\n",
       "      <td>39380735.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Album</td>\n",
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       "    <tr>\n",
       "      <th>18362792</th>\n",
       "      <td>Other</td>\n",
       "      <td>People</td>\n",
       "      <td>Person</td>\n",
       "      <td>0.990274</td>\n",
       "      <td>0.019795</td>\n",
       "      <td>Menasce</td>\n",
       "      <td>Daniel Menasce</td>\n",
       "      <td>Daniel Menasce</td>\n",
       "      <td>PERSON</td>\n",
       "      <td>None</td>\n",
       "      <td>People</td>\n",
       "      <td>None</td>\n",
       "      <td>38921168.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20987372</th>\n",
       "      <td>Other</td>\n",
       "      <td>Species</td>\n",
       "      <td>Eukaryote</td>\n",
       "      <td>0.991329</td>\n",
       "      <td>0.015792</td>\n",
       "      <td>Coelotes</td>\n",
       "      <td>Coelotes striatilamnis</td>\n",
       "      <td>Coelotes s. ketmenensis</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>None</td>\n",
       "      <td>Species</td>\n",
       "      <td>None</td>\n",
       "      <td>33212227.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31684226</th>\n",
       "      <td>Organisation</td>\n",
       "      <td>First World War</td>\n",
       "      <td>Organisation</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6th (United Kingdom) Division</td>\n",
       "      <td>6th (United Kingdom) Division--9th (Service)</td>\n",
       "      <td>9th (Service)</td>\n",
       "      <td>ORG</td>\n",
       "      <td>World War I</td>\n",
       "      <td>Later in the War</td>\n",
       "      <td>None</td>\n",
       "      <td>4250374.0</td>\n",
       "      <td>MilitaryConflict</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MilitaryUnit</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29948623</th>\n",
       "      <td>Work</td>\n",
       "      <td>Track listing</td>\n",
       "      <td>MusicalWork</td>\n",
       "      <td>0.943174</td>\n",
       "      <td>0.103822</td>\n",
       "      <td>A Picture of Me (Without You)</td>\n",
       "      <td>A Picture of Me (Without You)--She Loves Me (Right Out of My Mind)</td>\n",
       "      <td>She Loves Me (Right Out of My Mind)</td>\n",
       "      <td>WORK_OF_ART</td>\n",
       "      <td>None</td>\n",
       "      <td>Track listing</td>\n",
       "      <td>None</td>\n",
       "      <td>16758878.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Album</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9052004</th>\n",
       "      <td>Location</td>\n",
       "      <td>Stores</td>\n",
       "      <td>Company</td>\n",
       "      <td>0.983471</td>\n",
       "      <td>0.023047</td>\n",
       "      <td>Eastport Plaza</td>\n",
       "      <td>Eastport Plaza--Nail Tek</td>\n",
       "      <td>Nail Tek</td>\n",
       "      <td>ORG</td>\n",
       "      <td>None</td>\n",
       "      <td>Stores</td>\n",
       "      <td>None</td>\n",
       "      <td>30609099.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ShoppingMall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28487131</th>\n",
       "      <td>Work</td>\n",
       "      <td>Personnel</td>\n",
       "      <td>Artist</td>\n",
       "      <td>0.878850</td>\n",
       "      <td>0.140657</td>\n",
       "      <td>SimetriSiti</td>\n",
       "      <td>SimetriSiti--Jay Franco</td>\n",
       "      <td>Jay Franco</td>\n",
       "      <td>PERSON</td>\n",
       "      <td>None</td>\n",
       "      <td>Personnel</td>\n",
       "      <td>None</td>\n",
       "      <td>37829447.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Album</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34360607</th>\n",
       "      <td>Other</td>\n",
       "      <td>Rolling stock</td>\n",
       "      <td>MeanOfTransportation</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Kamome</td>\n",
       "      <td>Kamome--485 series EMUs</td>\n",
       "      <td>485 series EMUs</td>\n",
       "      <td>PRODUCT</td>\n",
       "      <td>None</td>\n",
       "      <td>Rolling stock used in the past</td>\n",
       "      <td>None</td>\n",
       "      <td>16899907.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21119704</th>\n",
       "      <td>Other</td>\n",
       "      <td>Species</td>\n",
       "      <td>Species</td>\n",
       "      <td>0.999608</td>\n",
       "      <td>0.002107</td>\n",
       "      <td>Gagea</td>\n",
       "      <td>Gagea hiensis</td>\n",
       "      <td>Gagea hiensis</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>None</td>\n",
       "      <td>Species</td>\n",
       "      <td>None</td>\n",
       "      <td>7517175.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2532341</th>\n",
       "      <td>List</td>\n",
       "      <td>Champions by year</td>\n",
       "      <td>Athlete</td>\n",
       "      <td>0.981884</td>\n",
       "      <td>0.112793</td>\n",
       "      <td>List of Grand Slam men's singles champions</td>\n",
       "      <td>Ashley Cooper (tennis player)</td>\n",
       "      <td>Ashley Cooper</td>\n",
       "      <td>PERSON</td>\n",
       "      <td>None</td>\n",
       "      <td>Champions by year</td>\n",
       "      <td>None</td>\n",
       "      <td>8457320.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>List</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28815210</th>\n",
       "      <td>Work</td>\n",
       "      <td>Personnel</td>\n",
       "      <td>MusicalArtist</td>\n",
       "      <td>0.871731</td>\n",
       "      <td>0.145537</td>\n",
       "      <td>Loud 'n' Raw</td>\n",
       "      <td>Loud 'n' Raw--Hirotsugu Homma</td>\n",
       "      <td>Hirotsugu Homma</td>\n",
       "      <td>PERSON</td>\n",
       "      <td>None</td>\n",
       "      <td>Personnel</td>\n",
       "      <td>None</td>\n",
       "      <td>25800546.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Album</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30777644</th>\n",
       "      <td>Work</td>\n",
       "      <td>Track listing</td>\n",
       "      <td>Song</td>\n",
       "      <td>0.888773</td>\n",
       "      <td>0.173072</td>\n",
       "      <td>Strange Blues</td>\n",
       "      <td>Strange Blues</td>\n",
       "      <td>Strange Blues</td>\n",
       "      <td>WORK_OF_ART</td>\n",
       "      <td>None</td>\n",
       "      <td>Track listing</td>\n",
       "      <td>None</td>\n",
       "      <td>32289269.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Album</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3295536</th>\n",
       "      <td>List</td>\n",
       "      <td>Forza Italia</td>\n",
       "      <td>Person</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>List of members of the Italian Senate, 1996–2001</td>\n",
       "      <td>Dino De Anna</td>\n",
       "      <td>Dino De Anna</td>\n",
       "      <td>PERSON</td>\n",
       "      <td>Forza Italia</td>\n",
       "      <td>Forza Italia</td>\n",
       "      <td>Forza Italia</td>\n",
       "      <td>33607227.0</td>\n",
       "      <td>PoliticalParty</td>\n",
       "      <td>PoliticalParty</td>\n",
       "      <td>List</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16237881</th>\n",
       "      <td>Other</td>\n",
       "      <td>Line of Succession</td>\n",
       "      <td>Agent</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Earl of Lonsdale</td>\n",
       "      <td>Earl of Lonsdale--Nikolas Lowther</td>\n",
       "      <td>Nikolas Lowther</td>\n",
       "      <td>PERSON</td>\n",
       "      <td>None</td>\n",
       "      <td>Line of Succession</td>\n",
       "      <td>None</td>\n",
       "      <td>3832509.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20650923</th>\n",
       "      <td>Other</td>\n",
       "      <td>Species</td>\n",
       "      <td>Animal</td>\n",
       "      <td>0.934213</td>\n",
       "      <td>0.151303</td>\n",
       "      <td>Neonoemacheilus</td>\n",
       "      <td>Neonoemacheilus morehensis</td>\n",
       "      <td>Neonoemacheilus morehensis</td>\n",
       "      <td>SPECIES</td>\n",
       "      <td>None</td>\n",
       "      <td>Species</td>\n",
       "      <td>None</td>\n",
       "      <td>29062922.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9728401</th>\n",
       "      <td>Organisation</td>\n",
       "      <td>Affiliated artists</td>\n",
       "      <td>Person</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>301Studios</td>\n",
       "      <td>301Studios--Max Haben</td>\n",
       "      <td>Max Haben</td>\n",
       "      <td>PERSON</td>\n",
       "      <td>None</td>\n",
       "      <td>Affiliated artists</td>\n",
       "      <td>None</td>\n",
       "      <td>20434515.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RecordLabel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28364375</th>\n",
       "      <td>Work</td>\n",
       "      <td>Personnel</td>\n",
       "      <td>Artist</td>\n",
       "      <td>0.878850</td>\n",
       "      <td>0.140657</td>\n",
       "      <td>Batbaby</td>\n",
       "      <td>Batbaby--Amy Luther</td>\n",
       "      <td>Amy Luther</td>\n",
       "      <td>PERSON</td>\n",
       "      <td>None</td>\n",
       "      <td>Personnel</td>\n",
       "      <td>None</td>\n",
       "      <td>29141603.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Album</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9212341</th>\n",
       "      <td>Location</td>\n",
       "      <td>Towns and villages in the district</td>\n",
       "      <td>PopulatedPlace</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Kottayam district</td>\n",
       "      <td>Kottayam district--Mudiyoorkara</td>\n",
       "      <td>Mudiyoorkara</td>\n",
       "      <td>GPE</td>\n",
       "      <td>None</td>\n",
       "      <td>Other villages</td>\n",
       "      <td>None</td>\n",
       "      <td>690614.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AdministrativeRegion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23163889</th>\n",
       "      <td>Person</td>\n",
       "      <td>Feature films</td>\n",
       "      <td>Work</td>\n",
       "      <td>0.995434</td>\n",
       "      <td>0.005732</td>\n",
       "      <td>Peggy McCay</td>\n",
       "      <td>Peggy McCay--Daddy's Girl</td>\n",
       "      <td>Daddy's Girl</td>\n",
       "      <td>WORK_OF_ART</td>\n",
       "      <td>None</td>\n",
       "      <td>Feature films</td>\n",
       "      <td>None</td>\n",
       "      <td>7372097.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Person</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31266144</th>\n",
       "      <td>Work</td>\n",
       "      <td>Track listing</td>\n",
       "      <td>Work</td>\n",
       "      <td>0.949392</td>\n",
       "      <td>0.093618</td>\n",
       "      <td>Regresará Por Mí</td>\n",
       "      <td>Regresará Por Mí--Tu Misericordia</td>\n",
       "      <td>Tu Misericordia</td>\n",
       "      <td>WORK_OF_ART</td>\n",
       "      <td>None</td>\n",
       "      <td>Track listing</td>\n",
       "      <td>None</td>\n",
       "      <td>27737421.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Album</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            P_basetype                             TS_text  \\\n",
       "29480310          Work                           Personnel   \n",
       "18362792         Other                              People   \n",
       "20987372         Other                             Species   \n",
       "31684226  Organisation                     First World War   \n",
       "29948623          Work                       Track listing   \n",
       "9052004       Location                              Stores   \n",
       "28487131          Work                           Personnel   \n",
       "34360607         Other                       Rolling stock   \n",
       "21119704         Other                             Species   \n",
       "2532341           List                   Champions by year   \n",
       "28815210          Work                           Personnel   \n",
       "30777644          Work                       Track listing   \n",
       "3295536           List                        Forza Italia   \n",
       "16237881         Other                  Line of Succession   \n",
       "20650923         Other                             Species   \n",
       "9728401   Organisation                  Affiliated artists   \n",
       "28364375          Work                           Personnel   \n",
       "9212341       Location  Towns and villages in the district   \n",
       "23163889        Person                       Feature films   \n",
       "31266144          Work                       Track listing   \n",
       "\n",
       "                     E_enttype  micro_mean  micro_std  \\\n",
       "29480310                Person    0.973151   0.045563   \n",
       "18362792                Person    0.990274   0.019795   \n",
       "20987372             Eukaryote    0.991329   0.015792   \n",
       "31684226          Organisation    1.000000   0.000000   \n",
       "29948623           MusicalWork    0.943174   0.103822   \n",
       "9052004                Company    0.983471   0.023047   \n",
       "28487131                Artist    0.878850   0.140657   \n",
       "34360607  MeanOfTransportation    1.000000   0.000000   \n",
       "21119704               Species    0.999608   0.002107   \n",
       "2532341                Athlete    0.981884   0.112793   \n",
       "28815210         MusicalArtist    0.871731   0.145537   \n",
       "30777644                  Song    0.888773   0.173072   \n",
       "3295536                 Person    1.000000   0.000000   \n",
       "16237881                 Agent    1.000000   0.000000   \n",
       "20650923                Animal    0.934213   0.151303   \n",
       "9728401                 Person    0.857143   0.000000   \n",
       "28364375                Artist    0.878850   0.140657   \n",
       "9212341         PopulatedPlace    1.000000   0.000000   \n",
       "23163889                  Work    0.995434   0.005732   \n",
       "31266144                  Work    0.949392   0.093618   \n",
       "\n",
       "                                                         P  \\\n",
       "29480310                                  Vanished Gardens   \n",
       "18362792                                           Menasce   \n",
       "20987372                                          Coelotes   \n",
       "31684226                     6th (United Kingdom) Division   \n",
       "29948623                     A Picture of Me (Without You)   \n",
       "9052004                                     Eastport Plaza   \n",
       "28487131                                       SimetriSiti   \n",
       "34360607                                            Kamome   \n",
       "21119704                                             Gagea   \n",
       "2532341         List of Grand Slam men's singles champions   \n",
       "28815210                                      Loud 'n' Raw   \n",
       "30777644                                     Strange Blues   \n",
       "3295536   List of members of the Italian Senate, 1996–2001   \n",
       "16237881                                  Earl of Lonsdale   \n",
       "20650923                                   Neonoemacheilus   \n",
       "9728401                                         301Studios   \n",
       "28364375                                           Batbaby   \n",
       "9212341                                  Kottayam district   \n",
       "23163889                                       Peggy McCay   \n",
       "31266144                                  Regresará Por Mí   \n",
       "\n",
       "                                                                       E_ent  \\\n",
       "29480310                                   Vanished Gardens--Bernie Grundman   \n",
       "18362792                                                      Daniel Menasce   \n",
       "20987372                                              Coelotes striatilamnis   \n",
       "31684226                        6th (United Kingdom) Division--9th (Service)   \n",
       "29948623  A Picture of Me (Without You)--She Loves Me (Right Out of My Mind)   \n",
       "9052004                                             Eastport Plaza--Nail Tek   \n",
       "28487131                                             SimetriSiti--Jay Franco   \n",
       "34360607                                             Kamome--485 series EMUs   \n",
       "21119704                                                       Gagea hiensis   \n",
       "2532341                                        Ashley Cooper (tennis player)   \n",
       "28815210                                       Loud 'n' Raw--Hirotsugu Homma   \n",
       "30777644                                                       Strange Blues   \n",
       "3295536                                                         Dino De Anna   \n",
       "16237881                                   Earl of Lonsdale--Nikolas Lowther   \n",
       "20650923                                          Neonoemacheilus morehensis   \n",
       "9728401                                                301Studios--Max Haben   \n",
       "28364375                                                 Batbaby--Amy Luther   \n",
       "9212341                                      Kottayam district--Mudiyoorkara   \n",
       "23163889                                           Peggy McCay--Daddy's Girl   \n",
       "31266144                                   Regresará Por Mí--Tu Misericordia   \n",
       "\n",
       "                                       E_text        E_tag        TS_ent  \\\n",
       "29480310                      Bernie Grundman       PERSON          None   \n",
       "18362792                       Daniel Menasce       PERSON          None   \n",
       "20987372              Coelotes s. ketmenensis        OTHER          None   \n",
       "31684226                        9th (Service)          ORG   World War I   \n",
       "29948623  She Loves Me (Right Out of My Mind)  WORK_OF_ART          None   \n",
       "9052004                              Nail Tek          ORG          None   \n",
       "28487131                           Jay Franco       PERSON          None   \n",
       "34360607                      485 series EMUs      PRODUCT          None   \n",
       "21119704                        Gagea hiensis        OTHER          None   \n",
       "2532341                         Ashley Cooper       PERSON          None   \n",
       "28815210                      Hirotsugu Homma       PERSON          None   \n",
       "30777644                        Strange Blues  WORK_OF_ART          None   \n",
       "3295536                          Dino De Anna       PERSON  Forza Italia   \n",
       "16237881                      Nikolas Lowther       PERSON          None   \n",
       "20650923           Neonoemacheilus morehensis      SPECIES          None   \n",
       "9728401                             Max Haben       PERSON          None   \n",
       "28364375                           Amy Luther       PERSON          None   \n",
       "9212341                          Mudiyoorkara          GPE          None   \n",
       "23163889                         Daddy's Girl  WORK_OF_ART          None   \n",
       "31266144                      Tu Misericordia  WORK_OF_ART          None   \n",
       "\n",
       "                                  S_text         S_ent        E_id  \\\n",
       "29480310                       Personnel          None  39380735.0   \n",
       "18362792                          People          None  38921168.0   \n",
       "20987372                         Species          None  33212227.0   \n",
       "31684226                Later in the War          None   4250374.0   \n",
       "29948623                   Track listing          None  16758878.0   \n",
       "9052004                           Stores          None  30609099.0   \n",
       "28487131                       Personnel          None  37829447.0   \n",
       "34360607  Rolling stock used in the past          None  16899907.0   \n",
       "21119704                         Species          None   7517175.0   \n",
       "2532341                Champions by year          None   8457320.0   \n",
       "28815210                       Personnel          None  25800546.0   \n",
       "30777644                   Track listing          None  32289269.0   \n",
       "3295536                     Forza Italia  Forza Italia  33607227.0   \n",
       "16237881              Line of Succession          None   3832509.0   \n",
       "20650923                         Species          None  29062922.0   \n",
       "9728401               Affiliated artists          None  20434515.0   \n",
       "28364375                       Personnel          None  29141603.0   \n",
       "9212341                   Other villages          None    690614.0   \n",
       "23163889                   Feature films          None   7372097.0   \n",
       "31266144                   Track listing          None  27737421.0   \n",
       "\n",
       "                TS_enttype       S_enttype                P_type  \n",
       "29480310               NaN             NaN                 Album  \n",
       "18362792               NaN             NaN                 Other  \n",
       "20987372               NaN             NaN                 Other  \n",
       "31684226  MilitaryConflict             NaN          MilitaryUnit  \n",
       "29948623               NaN             NaN                 Album  \n",
       "9052004                NaN             NaN          ShoppingMall  \n",
       "28487131               NaN             NaN                 Album  \n",
       "34360607               NaN             NaN                 Other  \n",
       "21119704               NaN             NaN                 Other  \n",
       "2532341                NaN             NaN                  List  \n",
       "28815210               NaN             NaN                 Album  \n",
       "30777644               NaN             NaN                 Album  \n",
       "3295536     PoliticalParty  PoliticalParty                  List  \n",
       "16237881               NaN             NaN                 Other  \n",
       "20650923               NaN             NaN                 Other  \n",
       "9728401                NaN             NaN           RecordLabel  \n",
       "28364375               NaN             NaN                 Album  \n",
       "9212341                NaN             NaN  AdministrativeRegion  \n",
       "23163889               NaN             NaN                Person  \n",
       "31266144               NaN             NaN                 Album  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_types_dbp.sample(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>E_text</th>\n",
       "      <th>E_enttype</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14654325</th>\n",
       "      <td>Nicolae Negumereanu</td>\n",
       "      <td>MartialArtist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29470332</th>\n",
       "      <td>Ergun</td>\n",
       "      <td>Person</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14416762</th>\n",
       "      <td>Nilkanth Singh Munda</td>\n",
       "      <td>Politician</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21230683</th>\n",
       "      <td>Medetera valaisensis</td>\n",
       "      <td>Species</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24549197</th>\n",
       "      <td>Daïnah la métisse</td>\n",
       "      <td>Work</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29966481</th>\n",
       "      <td>Steady Rain</td>\n",
       "      <td>MusicalWork</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15827202</th>\n",
       "      <td>Harry Weisberg</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30065800</th>\n",
       "      <td>Slide Show</td>\n",
       "      <td>MusicalWork</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26804418</th>\n",
       "      <td>Amelia Wiśniewska</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29313304</th>\n",
       "      <td>Joshua Levy-</td>\n",
       "      <td>Person</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32285183</th>\n",
       "      <td>Maeght Foundation</td>\n",
       "      <td>ArchitecturalStructure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212625</th>\n",
       "      <td>Mars Matrix</td>\n",
       "      <td>VideoGame</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28654942</th>\n",
       "      <td>Chris Laws</td>\n",
       "      <td>MusicalArtist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35334405</th>\n",
       "      <td>The Tigress</td>\n",
       "      <td>Film</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29280036</th>\n",
       "      <td>A. J. Benson</td>\n",
       "      <td>Person</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3270801</th>\n",
       "      <td>Art DeCarlo</td>\n",
       "      <td>GridironFootballPlayer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3806127</th>\n",
       "      <td>KENH-LD</td>\n",
       "      <td>Broadcaster</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20592007</th>\n",
       "      <td>Euclystis golosus</td>\n",
       "      <td>Animal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>909124</th>\n",
       "      <td>Alina Gracheva</td>\n",
       "      <td>Person</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14001821</th>\n",
       "      <td>Leadbetter</td>\n",
       "      <td>SnookerPlayer</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        E_text               E_enttype\n",
       "14654325   Nicolae Negumereanu           MartialArtist\n",
       "29470332                 Ergun                  Person\n",
       "14416762  Nilkanth Singh Munda              Politician\n",
       "21230683  Medetera valaisensis                 Species\n",
       "24549197     Daïnah la métisse                    Work\n",
       "29966481           Steady Rain             MusicalWork\n",
       "15827202        Harry Weisberg                   Agent\n",
       "30065800            Slide Show             MusicalWork\n",
       "26804418     Amelia Wiśniewska                   Agent\n",
       "29313304          Joshua Levy-                  Person\n",
       "32285183     Maeght Foundation  ArchitecturalStructure\n",
       "212625             Mars Matrix               VideoGame\n",
       "28654942            Chris Laws           MusicalArtist\n",
       "35334405           The Tigress                    Film\n",
       "29280036          A. J. Benson                  Person\n",
       "3270801            Art DeCarlo  GridironFootballPlayer\n",
       "3806127                KENH-LD             Broadcaster\n",
       "20592007     Euclystis golosus                  Animal\n",
       "909124          Alina Gracheva                  Person\n",
       "14001821            Leadbetter           SnookerPlayer"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_types_dbp.sample(20)[['E_text', 'E_enttype']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# write new types to file\n",
    "def serialize_types_dbp(df, filename):\n",
    "    triples = [serialize_util.as_object_triple(dbp_util.name2resource(r['E_ent']), rdf_util.PREDICATE_TYPE, dbp_util.name2type(r['E_enttype'])) for _, r in df.iterrows()]\n",
    "    with open(filename, mode='w') as f:\n",
    "        f.writelines(triples)\n",
    "\n",
    "serialize_types_dbp(filtered_types_dbp, 'new_types_dbpedia.nt')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Type Extraction for *CaLiGraph*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute valid combinations of types and NE tags\n",
    "\n",
    "df_types_clg = context.get_entity_types(df, graph)\n",
    "dft_clg = pd.merge(left=df, right=df_types_clg, on='E_ent')\n",
    "valid_tags_clg = context.get_valid_tags_for_entity_types(dft_clg, graph, .35)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract rules\n",
    "\n",
    "rule_dfs_clg = {}\n",
    "for rule_name, rule_pattern in extract.RULE_PATTERNS.items():\n",
    "    dft_by_page = extract._aggregate_types_by_page(dft_clg, rule_pattern)\n",
    "    rule_dfs_clg[rule_name] = extract._aggregate_types_by_section(dft_by_page, rule_pattern)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# filter rules by threshold and compute filtered types\n",
    "\n",
    "new_types_clg = extract._extract_new_types_with_threshold(df, df_types_clg, rule_dfs_clg)\n",
    "filtered_types_clg = extract._filter_new_types_by_tag(new_types_clg, valid_tags_clg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# write new types to file\n",
    "\n",
    "def serialize_types_clg(df, filename):\n",
    "    triples = [serialize_util.as_object_triple(clg_util.name2clg_resource(r['E_ent']), rdf_util.PREDICATE_TYPE, clg_util.name2clg_type(r['E_enttype'])) for _, r in df.iterrows()]\n",
    "    with open(filename, mode='w') as f:\n",
    "        f.writelines(triples)\n",
    "\n",
    "serialize_types_clg(filtered_types_clg, 'new_types_caligraph.nt')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Relation Extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# retrieve existing relations\n",
    "\n",
    "df_rels = context.get_entity_relations()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Threshold Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract all possible rules for relations with PageEntity as target\n",
    "\n",
    "rule_dfs = {}\n",
    "dfr = extract._create_relation_df(df, df_rels, 'P')\n",
    "dfr_types = extract._create_relation_type_df(dfr)\n",
    "for rule_name, rule_pattern in extract.RULE_PATTERNS.items():\n",
    "    dfr_by_page = extract._aggregate_relations_by_page(df, dfr, df_rels, rule_pattern)\n",
    "    rule_dfs[rule_name] = extract._aggregate_relations_by_section(dfr_by_page, rule_pattern)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# generate all possible relations up to a very low threshold (mean > 0.25 and std < 0.75)\n",
    "threshold_rule_dfs = [rule_dfs[rule_name].query(f'page_count > 2 & micro_mean > .25 & micro_std < .75').reset_index()[rule_pattern + ['rel', 'micro_mean', 'micro_std']].drop_duplicates() for rule_name, rule_pattern in extract.RULE_PATTERNS.items()]\n",
    "threshold_relations = extract._extract_new_relations(threshold_rule_dfs, 'P', df, dfr_types, df_rels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualise thresholds\n",
    "\n",
    "def visualise_relation_thresholds(df, target, tag_probabilities, bin_count):    \n",
    "    \"\"\"Visualize the tag fit in relation to the confidence and consistency (here: std).\"\"\"\n",
    "    # add tag_fit\n",
    "    df = pd.merge(df, tag_probabilities, left_on=['E_predtype', 'E_tag'], right_on=['E_enttype', 'E_tag'])\n",
    "    \n",
    "    min_mean = .25\n",
    "    mean_conf_labels = [min_mean + x / bin_count * (1 - min_mean) for x in range(bin_count)]\n",
    "    df['mean_confidence'] = pd.cut(df['micro_mean'], bin_count, labels=mean_conf_labels)\n",
    "    max_std = .75\n",
    "    std_conf_labels = [(x+1) / bin_count * max_std for x in range(bin_count)]\n",
    "    df['std_confidence'] = pd.cut(df['micro_std'], bin_count, labels=std_conf_labels)\n",
    "    \n",
    "    ## tag_fit with confidence ##\n",
    "    # per bin\n",
    "    plt.bar(x=mean_conf_labels, height=df.groupby('mean_confidence')['tag_fit'].mean().values, width=(1-min_mean)/bin_count*0.8, align='edge', label='tag_fit')\n",
    "    # cumulative\n",
    "    cumulative_tag_fit = [df[df['micro_mean'] > x]['tag_fit'].mean() for x in mean_conf_labels]\n",
    "    plt.plot(mean_conf_labels, cumulative_tag_fit, 'ro--', label='tag_fit (cum)')\n",
    "    plt.xlabel('Pattern Confidence')\n",
    "    plt.title('Pattern Confidence vs. Tagger Confidence')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    \n",
    "    ## tag_fit with consistency ##\n",
    "    # per bin\n",
    "    plt.bar(x=std_conf_labels, height=df.groupby('std_confidence')['tag_fit'].mean().values, width=max_std/bin_count*-0.8, align='edge', label='tag_fit')\n",
    "    # cumulative\n",
    "    cumulative_tag_fit = [df[df['micro_std'] < x]['tag_fit'].mean() for x in std_conf_labels]\n",
    "    plt.plot(std_conf_labels, cumulative_tag_fit, 'ro--', label='tag_fit (cum)')\n",
    "    plt.xlabel('Pattern Std.Dev.')\n",
    "    plt.title('Pattern Std.Dev. vs. Tagger Confidence')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    \n",
    "visualise_relation_thresholds(threshold_relations, 'P', context._get_tag_probabilities(dft_dbp), 15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# retrieve new relations for all three targets\n",
    "df_new_relations = extract._compute_new_relations(df, df_rels, 'P', valid_tags_dbp)\n",
    "df_new_relations = pd.concat([df_new_relations, extract._compute_new_relations(df, df_rels, 'TS_ent', valid_tags_dbp)])\n",
    "df_new_relations = pd.concat([df_new_relations, extract._compute_new_relations(df, df_rels, 'S_ent', valid_tags_dbp)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>P_basetype</th>\n",
       "      <th>TS_text</th>\n",
       "      <th>rel</th>\n",
       "      <th>micro_mean</th>\n",
       "      <th>micro_std</th>\n",
       "      <th>P</th>\n",
       "      <th>E_ent</th>\n",
       "      <th>E_text</th>\n",
       "      <th>E_tag</th>\n",
       "      <th>TS_ent</th>\n",
       "      <th>S_text</th>\n",
       "      <th>S_ent</th>\n",
       "      <th>E_id</th>\n",
       "      <th>TS_enttype</th>\n",
       "      <th>S_enttype</th>\n",
       "      <th>P_type</th>\n",
       "      <th>pred</th>\n",
       "      <th>inv</th>\n",
       "      <th>E_predtype</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1804314</th>\n",
       "      <td>Other</td>\n",
       "      <td>Species</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>0.977019</td>\n",
       "      <td>0.045419</td>\n",
       "      <td>Halimuraena</td>\n",
       "      <td>Halimuraena shakai</td>\n",
       "      <td>Halimuraena shakai</td>\n",
       "      <td>SPECIES</td>\n",
       "      <td>None</td>\n",
       "      <td>Species</td>\n",
       "      <td>None</td>\n",
       "      <td>39648306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>http://dbpedia.org/ontology/genus</td>\n",
       "      <td>True</td>\n",
       "      <td>Species</td>\n",
       "      <td>Halimuraena</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216985</th>\n",
       "      <td>Location</td>\n",
       "      <td>Communities</td>\n",
       "      <td>&lt; subdivision &lt;</td>\n",
       "      <td>0.957367</td>\n",
       "      <td>0.098188</td>\n",
       "      <td>Christian County, Missouri</td>\n",
       "      <td>Chadwick, Missouri</td>\n",
       "      <td>Chadwick</td>\n",
       "      <td>GPE</td>\n",
       "      <td>None</td>\n",
       "      <td>Other unincorporated communities</td>\n",
       "      <td>None</td>\n",
       "      <td>1353294</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AdministrativeRegion</td>\n",
       "      <td>http://dbpedia.org/ontology/subdivision</td>\n",
       "      <td>True</td>\n",
       "      <td>PopulatedPlace</td>\n",
       "      <td>Christian County, Missouri</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107055</th>\n",
       "      <td>List</td>\n",
       "      <td>Odonata</td>\n",
       "      <td>&lt; order &lt;</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>List of least concern insects</td>\n",
       "      <td>Pinheyschna subpupillata</td>\n",
       "      <td>Stream hawker</td>\n",
       "      <td>SPECIES</td>\n",
       "      <td>Odonata</td>\n",
       "      <td>Aeshnids</td>\n",
       "      <td>Aeshnidae</td>\n",
       "      <td>36319656</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>List</td>\n",
       "      <td>http://dbpedia.org/ontology/order</td>\n",
       "      <td>True</td>\n",
       "      <td>Species</td>\n",
       "      <td>Odonata</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1650594</th>\n",
       "      <td>Other</td>\n",
       "      <td>Species</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>0.977019</td>\n",
       "      <td>0.045419</td>\n",
       "      <td>Eupoecilia</td>\n",
       "      <td>Eupoecilia kruegeriana</td>\n",
       "      <td>Eupoecilia kruegeriana</td>\n",
       "      <td>SPECIES</td>\n",
       "      <td>None</td>\n",
       "      <td>Species</td>\n",
       "      <td>None</td>\n",
       "      <td>25698774</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>http://dbpedia.org/ontology/genus</td>\n",
       "      <td>True</td>\n",
       "      <td>Species</td>\n",
       "      <td>Eupoecilia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61042</th>\n",
       "      <td>List</td>\n",
       "      <td>Gastropods</td>\n",
       "      <td>&lt; family &lt;</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>List of vulnerable molluscs</td>\n",
       "      <td>Brotia wykoffi</td>\n",
       "      <td>Brotia wykoffi</td>\n",
       "      <td>SPECIES</td>\n",
       "      <td>Gastropoda</td>\n",
       "      <td>Pachychilids</td>\n",
       "      <td>Pachychilidae</td>\n",
       "      <td>36300492</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>List</td>\n",
       "      <td>http://dbpedia.org/ontology/family</td>\n",
       "      <td>True</td>\n",
       "      <td>Species</td>\n",
       "      <td>Pachychilidae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1732647</th>\n",
       "      <td>Other</td>\n",
       "      <td>Species</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>0.977019</td>\n",
       "      <td>0.045419</td>\n",
       "      <td>Leptoneta</td>\n",
       "      <td>Leptoneta maculosa</td>\n",
       "      <td>L. maculosa</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>None</td>\n",
       "      <td>Species</td>\n",
       "      <td>None</td>\n",
       "      <td>37360208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>http://dbpedia.org/ontology/genus</td>\n",
       "      <td>True</td>\n",
       "      <td>Species</td>\n",
       "      <td>Leptoneta</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2084439</th>\n",
       "      <td>Species</td>\n",
       "      <td>Species</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>0.984059</td>\n",
       "      <td>0.029726</td>\n",
       "      <td>Triphora (gastropod)</td>\n",
       "      <td>Triphora dalli</td>\n",
       "      <td>Triphora dalli</td>\n",
       "      <td>SPECIES</td>\n",
       "      <td>Species</td>\n",
       "      <td>Species</td>\n",
       "      <td>Species</td>\n",
       "      <td>32364528</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mollusca</td>\n",
       "      <td>http://dbpedia.org/ontology/genus</td>\n",
       "      <td>True</td>\n",
       "      <td>Species</td>\n",
       "      <td>Triphora (gastropod)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>654105</th>\n",
       "      <td>Person</td>\n",
       "      <td>Directing filmography</td>\n",
       "      <td>&lt; director &lt;</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Jonathan Frakes</td>\n",
       "      <td>Jonathan Frakes--All or Nothing</td>\n",
       "      <td>All or Nothing</td>\n",
       "      <td>WORK_OF_ART</td>\n",
       "      <td>None</td>\n",
       "      <td>Television</td>\n",
       "      <td>None</td>\n",
       "      <td>1103264</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Person</td>\n",
       "      <td>http://dbpedia.org/ontology/director</td>\n",
       "      <td>True</td>\n",
       "      <td>Film</td>\n",
       "      <td>Jonathan Frakes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>806033</th>\n",
       "      <td>Person</td>\n",
       "      <td>Film scores</td>\n",
       "      <td>&lt; musicComposer &lt;</td>\n",
       "      <td>0.873288</td>\n",
       "      <td>0.154829</td>\n",
       "      <td>Don Preston</td>\n",
       "      <td>The Underachievers (film)</td>\n",
       "      <td>The Underachievers</td>\n",
       "      <td>WORK_OF_ART</td>\n",
       "      <td>None</td>\n",
       "      <td>Film scores</td>\n",
       "      <td>None</td>\n",
       "      <td>12602413</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MusicalArtist</td>\n",
       "      <td>http://dbpedia.org/ontology/musicComposer</td>\n",
       "      <td>True</td>\n",
       "      <td>Work</td>\n",
       "      <td>Don Preston</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611381</th>\n",
       "      <td>Organisation</td>\n",
       "      <td>Singles</td>\n",
       "      <td>&lt; artist &lt;</td>\n",
       "      <td>0.903226</td>\n",
       "      <td>0.130987</td>\n",
       "      <td>La Factoría</td>\n",
       "      <td>La Factoría--Amiga</td>\n",
       "      <td>Amiga</td>\n",
       "      <td>WORK_OF_ART</td>\n",
       "      <td>None</td>\n",
       "      <td>Singles</td>\n",
       "      <td>None</td>\n",
       "      <td>21081955</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Band</td>\n",
       "      <td>http://dbpedia.org/ontology/artist</td>\n",
       "      <td>True</td>\n",
       "      <td>MusicalWork</td>\n",
       "      <td>La Factoría</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1509909</th>\n",
       "      <td>Other</td>\n",
       "      <td>Species</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>0.977019</td>\n",
       "      <td>0.045419</td>\n",
       "      <td>Mouse-eared bat</td>\n",
       "      <td>Myotis oxyotus</td>\n",
       "      <td>Myotis oxyotus</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>None</td>\n",
       "      <td>Species</td>\n",
       "      <td>None</td>\n",
       "      <td>8796526</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>http://dbpedia.org/ontology/genus</td>\n",
       "      <td>True</td>\n",
       "      <td>Species</td>\n",
       "      <td>Mouse-eared bat</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1226829</th>\n",
       "      <td>Species</td>\n",
       "      <td>Main</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>0.985182</td>\n",
       "      <td>0.098228</td>\n",
       "      <td>Apristus</td>\n",
       "      <td>Apristus striatus</td>\n",
       "      <td>Apristus striatus</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>None</td>\n",
       "      <td>Main</td>\n",
       "      <td>None</td>\n",
       "      <td>28762634</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Insect</td>\n",
       "      <td>http://dbpedia.org/ontology/genus</td>\n",
       "      <td>True</td>\n",
       "      <td>Species</td>\n",
       "      <td>Apristus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>385490</th>\n",
       "      <td>Location</td>\n",
       "      <td>Communities</td>\n",
       "      <td>&lt; subdivision &lt;</td>\n",
       "      <td>0.980844</td>\n",
       "      <td>0.034299</td>\n",
       "      <td>Arkansas County, Arkansas</td>\n",
       "      <td>Nady, Arkansas</td>\n",
       "      <td>Nady</td>\n",
       "      <td>GPE</td>\n",
       "      <td>None</td>\n",
       "      <td>Unincorporated communities</td>\n",
       "      <td>None</td>\n",
       "      <td>1240891</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AdministrativeRegion</td>\n",
       "      <td>http://dbpedia.org/ontology/subdivision</td>\n",
       "      <td>True</td>\n",
       "      <td>PopulatedPlace</td>\n",
       "      <td>Arkansas County, Arkansas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>795111</th>\n",
       "      <td>Person</td>\n",
       "      <td>Works</td>\n",
       "      <td>&lt; author &lt;</td>\n",
       "      <td>0.958395</td>\n",
       "      <td>0.199014</td>\n",
       "      <td>Krishna Sobti</td>\n",
       "      <td>Krishna Sobti--Badalon</td>\n",
       "      <td>Badalon</td>\n",
       "      <td>WORK_OF_ART</td>\n",
       "      <td>None</td>\n",
       "      <td>Novels</td>\n",
       "      <td>None</td>\n",
       "      <td>20960058</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Writer</td>\n",
       "      <td>http://dbpedia.org/ontology/author</td>\n",
       "      <td>True</td>\n",
       "      <td>Work</td>\n",
       "      <td>Krishna Sobti</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63260</th>\n",
       "      <td>List</td>\n",
       "      <td>Insects</td>\n",
       "      <td>&lt; family &lt;</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>List of least concern arthropods</td>\n",
       "      <td>Micrathyria caerulistyla</td>\n",
       "      <td>Blue-tipped dasher</td>\n",
       "      <td>SPECIES</td>\n",
       "      <td>Insect</td>\n",
       "      <td>Libellulids</td>\n",
       "      <td>Libellulidae</td>\n",
       "      <td>36130044</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>List</td>\n",
       "      <td>http://dbpedia.org/ontology/family</td>\n",
       "      <td>True</td>\n",
       "      <td>Species</td>\n",
       "      <td>Libellulidae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285621</th>\n",
       "      <td>Work</td>\n",
       "      <td>Personnel</td>\n",
       "      <td>&lt; associatedBand &lt;</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>The Real Thing (Midnight Oil album)</td>\n",
       "      <td>Bones Hillman</td>\n",
       "      <td>Bones Hillman</td>\n",
       "      <td>PERSON</td>\n",
       "      <td>None</td>\n",
       "      <td>Midnight Oil</td>\n",
       "      <td>Midnight Oil</td>\n",
       "      <td>10413938</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Agent</td>\n",
       "      <td>Album</td>\n",
       "      <td>http://dbpedia.org/ontology/associatedBand</td>\n",
       "      <td>True</td>\n",
       "      <td>Agent</td>\n",
       "      <td>Midnight Oil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61849</th>\n",
       "      <td>List</td>\n",
       "      <td>Molluscs</td>\n",
       "      <td>&lt; phylum &lt;</td>\n",
       "      <td>0.907692</td>\n",
       "      <td>0.043341</td>\n",
       "      <td>List of endangered invertebrates</td>\n",
       "      <td>Hadopyrgus brevis</td>\n",
       "      <td>Hadopyrgus brevis</td>\n",
       "      <td>SPECIES</td>\n",
       "      <td>Mollusca</td>\n",
       "      <td>Hydrobiids</td>\n",
       "      <td>Hydrobiidae</td>\n",
       "      <td>36240302</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>List</td>\n",
       "      <td>http://dbpedia.org/ontology/phylum</td>\n",
       "      <td>True</td>\n",
       "      <td>Species</td>\n",
       "      <td>Mollusca</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20940</th>\n",
       "      <td>Person</td>\n",
       "      <td>Career statistics</td>\n",
       "      <td>&gt; team &gt;</td>\n",
       "      <td>0.931480</td>\n",
       "      <td>0.106772</td>\n",
       "      <td>Joe Ledley</td>\n",
       "      <td>Joe Ledley--Newcastle</td>\n",
       "      <td>Newcastle</td>\n",
       "      <td>ORG</td>\n",
       "      <td>None</td>\n",
       "      <td>Career statistics</td>\n",
       "      <td>None</td>\n",
       "      <td>10472566</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SoccerPlayer</td>\n",
       "      <td>http://dbpedia.org/ontology/team</td>\n",
       "      <td>False</td>\n",
       "      <td>SportsTeam</td>\n",
       "      <td>Joe Ledley</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>688946</th>\n",
       "      <td>Person</td>\n",
       "      <td>Partial filmography</td>\n",
       "      <td>&lt; director &lt;</td>\n",
       "      <td>0.922360</td>\n",
       "      <td>0.164080</td>\n",
       "      <td>George Hill (director)</td>\n",
       "      <td>Min and Bill</td>\n",
       "      <td>Min and Bill</td>\n",
       "      <td>WORK_OF_ART</td>\n",
       "      <td>None</td>\n",
       "      <td>Director</td>\n",
       "      <td>None</td>\n",
       "      <td>9569050</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Person</td>\n",
       "      <td>http://dbpedia.org/ontology/director</td>\n",
       "      <td>True</td>\n",
       "      <td>Film</td>\n",
       "      <td>George Hill (director)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1480502</th>\n",
       "      <td>Other</td>\n",
       "      <td>List of species</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>0.987805</td>\n",
       "      <td>0.021681</td>\n",
       "      <td>Cybister</td>\n",
       "      <td>Cybister crassipes</td>\n",
       "      <td>Cybister crassipes</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>None</td>\n",
       "      <td>List of species</td>\n",
       "      <td>None</td>\n",
       "      <td>24520612</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>http://dbpedia.org/ontology/genus</td>\n",
       "      <td>True</td>\n",
       "      <td>Species</td>\n",
       "      <td>Cybister</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           P_basetype                TS_text                 rel  micro_mean  \\\n",
       "1804314         Other                Species           < genus <    0.977019   \n",
       "216985       Location            Communities     < subdivision <    0.957367   \n",
       "107055           List                Odonata           < order <    1.000000   \n",
       "1650594         Other                Species           < genus <    0.977019   \n",
       "61042            List             Gastropods          < family <    1.000000   \n",
       "1732647         Other                Species           < genus <    0.977019   \n",
       "2084439       Species                Species           < genus <    0.984059   \n",
       "654105         Person  Directing filmography        < director <    1.000000   \n",
       "806033         Person            Film scores   < musicComposer <    0.873288   \n",
       "611381   Organisation                Singles          < artist <    0.903226   \n",
       "1509909         Other                Species           < genus <    0.977019   \n",
       "1226829       Species                   Main           < genus <    0.985182   \n",
       "385490       Location            Communities     < subdivision <    0.980844   \n",
       "795111         Person                  Works          < author <    0.958395   \n",
       "63260            List                Insects          < family <    1.000000   \n",
       "285621           Work              Personnel  < associatedBand <    1.000000   \n",
       "61849            List               Molluscs          < phylum <    0.907692   \n",
       "20940          Person      Career statistics            > team >    0.931480   \n",
       "688946         Person    Partial filmography        < director <    0.922360   \n",
       "1480502         Other        List of species           < genus <    0.987805   \n",
       "\n",
       "         micro_std                                    P  \\\n",
       "1804314   0.045419                          Halimuraena   \n",
       "216985    0.098188           Christian County, Missouri   \n",
       "107055    0.000000        List of least concern insects   \n",
       "1650594   0.045419                           Eupoecilia   \n",
       "61042     0.000000          List of vulnerable molluscs   \n",
       "1732647   0.045419                            Leptoneta   \n",
       "2084439   0.029726                 Triphora (gastropod)   \n",
       "654105    0.000000                      Jonathan Frakes   \n",
       "806033    0.154829                          Don Preston   \n",
       "611381    0.130987                          La Factoría   \n",
       "1509909   0.045419                      Mouse-eared bat   \n",
       "1226829   0.098228                             Apristus   \n",
       "385490    0.034299            Arkansas County, Arkansas   \n",
       "795111    0.199014                        Krishna Sobti   \n",
       "63260     0.000000     List of least concern arthropods   \n",
       "285621    0.000000  The Real Thing (Midnight Oil album)   \n",
       "61849     0.043341     List of endangered invertebrates   \n",
       "20940     0.106772                           Joe Ledley   \n",
       "688946    0.164080               George Hill (director)   \n",
       "1480502   0.021681                             Cybister   \n",
       "\n",
       "                                   E_ent                  E_text        E_tag  \\\n",
       "1804314               Halimuraena shakai      Halimuraena shakai      SPECIES   \n",
       "216985                Chadwick, Missouri                Chadwick          GPE   \n",
       "107055          Pinheyschna subpupillata           Stream hawker      SPECIES   \n",
       "1650594           Eupoecilia kruegeriana  Eupoecilia kruegeriana      SPECIES   \n",
       "61042                     Brotia wykoffi          Brotia wykoffi      SPECIES   \n",
       "1732647               Leptoneta maculosa             L. maculosa        OTHER   \n",
       "2084439                   Triphora dalli          Triphora dalli      SPECIES   \n",
       "654105   Jonathan Frakes--All or Nothing          All or Nothing  WORK_OF_ART   \n",
       "806033         The Underachievers (film)      The Underachievers  WORK_OF_ART   \n",
       "611381                La Factoría--Amiga                   Amiga  WORK_OF_ART   \n",
       "1509909                   Myotis oxyotus          Myotis oxyotus        OTHER   \n",
       "1226829                Apristus striatus       Apristus striatus        OTHER   \n",
       "385490                    Nady, Arkansas                    Nady          GPE   \n",
       "795111            Krishna Sobti--Badalon                 Badalon  WORK_OF_ART   \n",
       "63260           Micrathyria caerulistyla      Blue-tipped dasher      SPECIES   \n",
       "285621                     Bones Hillman           Bones Hillman       PERSON   \n",
       "61849                  Hadopyrgus brevis       Hadopyrgus brevis      SPECIES   \n",
       "20940              Joe Ledley--Newcastle               Newcastle          ORG   \n",
       "688946                      Min and Bill            Min and Bill  WORK_OF_ART   \n",
       "1480502               Cybister crassipes      Cybister crassipes        OTHER   \n",
       "\n",
       "             TS_ent                            S_text          S_ent  \\\n",
       "1804314        None                           Species           None   \n",
       "216985         None  Other unincorporated communities           None   \n",
       "107055      Odonata                          Aeshnids      Aeshnidae   \n",
       "1650594        None                           Species           None   \n",
       "61042    Gastropoda                      Pachychilids  Pachychilidae   \n",
       "1732647        None                           Species           None   \n",
       "2084439     Species                           Species        Species   \n",
       "654105         None                        Television           None   \n",
       "806033         None                       Film scores           None   \n",
       "611381         None                           Singles           None   \n",
       "1509909        None                           Species           None   \n",
       "1226829        None                              Main           None   \n",
       "385490         None        Unincorporated communities           None   \n",
       "795111         None                            Novels           None   \n",
       "63260        Insect                       Libellulids   Libellulidae   \n",
       "285621         None                      Midnight Oil   Midnight Oil   \n",
       "61849      Mollusca                        Hydrobiids    Hydrobiidae   \n",
       "20940          None                 Career statistics           None   \n",
       "688946         None                          Director           None   \n",
       "1480502        None                   List of species           None   \n",
       "\n",
       "             E_id TS_enttype S_enttype                P_type  \\\n",
       "1804314  39648306        NaN       NaN                 Other   \n",
       "216985    1353294        NaN       NaN  AdministrativeRegion   \n",
       "107055   36319656        NaN       NaN                  List   \n",
       "1650594  25698774        NaN       NaN                 Other   \n",
       "61042    36300492        NaN       NaN                  List   \n",
       "1732647  37360208        NaN       NaN                 Other   \n",
       "2084439  32364528        NaN       NaN              Mollusca   \n",
       "654105    1103264        NaN       NaN                Person   \n",
       "806033   12602413        NaN       NaN         MusicalArtist   \n",
       "611381   21081955        NaN       NaN                  Band   \n",
       "1509909   8796526        NaN       NaN                 Other   \n",
       "1226829  28762634        NaN       NaN                Insect   \n",
       "385490    1240891        NaN       NaN  AdministrativeRegion   \n",
       "795111   20960058        NaN       NaN                Writer   \n",
       "63260    36130044        NaN       NaN                  List   \n",
       "285621   10413938        NaN     Agent                 Album   \n",
       "61849    36240302        NaN       NaN                  List   \n",
       "20940    10472566        NaN       NaN          SoccerPlayer   \n",
       "688946    9569050        NaN       NaN                Person   \n",
       "1480502  24520612        NaN       NaN                 Other   \n",
       "\n",
       "                                               pred    inv      E_predtype  \\\n",
       "1804314           http://dbpedia.org/ontology/genus   True         Species   \n",
       "216985      http://dbpedia.org/ontology/subdivision   True  PopulatedPlace   \n",
       "107055            http://dbpedia.org/ontology/order   True         Species   \n",
       "1650594           http://dbpedia.org/ontology/genus   True         Species   \n",
       "61042            http://dbpedia.org/ontology/family   True         Species   \n",
       "1732647           http://dbpedia.org/ontology/genus   True         Species   \n",
       "2084439           http://dbpedia.org/ontology/genus   True         Species   \n",
       "654105         http://dbpedia.org/ontology/director   True            Film   \n",
       "806033    http://dbpedia.org/ontology/musicComposer   True            Work   \n",
       "611381           http://dbpedia.org/ontology/artist   True     MusicalWork   \n",
       "1509909           http://dbpedia.org/ontology/genus   True         Species   \n",
       "1226829           http://dbpedia.org/ontology/genus   True         Species   \n",
       "385490      http://dbpedia.org/ontology/subdivision   True  PopulatedPlace   \n",
       "795111           http://dbpedia.org/ontology/author   True            Work   \n",
       "63260            http://dbpedia.org/ontology/family   True         Species   \n",
       "285621   http://dbpedia.org/ontology/associatedBand   True           Agent   \n",
       "61849            http://dbpedia.org/ontology/phylum   True         Species   \n",
       "20940              http://dbpedia.org/ontology/team  False      SportsTeam   \n",
       "688946         http://dbpedia.org/ontology/director   True            Film   \n",
       "1480502           http://dbpedia.org/ontology/genus   True         Species   \n",
       "\n",
       "                             target  \n",
       "1804314                 Halimuraena  \n",
       "216985   Christian County, Missouri  \n",
       "107055                      Odonata  \n",
       "1650594                  Eupoecilia  \n",
       "61042                 Pachychilidae  \n",
       "1732647                   Leptoneta  \n",
       "2084439        Triphora (gastropod)  \n",
       "654105              Jonathan Frakes  \n",
       "806033                  Don Preston  \n",
       "611381                  La Factoría  \n",
       "1509909             Mouse-eared bat  \n",
       "1226829                    Apristus  \n",
       "385490    Arkansas County, Arkansas  \n",
       "795111                Krishna Sobti  \n",
       "63260                  Libellulidae  \n",
       "285621                 Midnight Oil  \n",
       "61849                      Mollusca  \n",
       "20940                    Joe Ledley  \n",
       "688946       George Hill (director)  \n",
       "1480502                    Cybister  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new_relations.sample(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>target</th>\n",
       "      <th>rel</th>\n",
       "      <th>E_text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>274906</th>\n",
       "      <td>Sturgeon County</td>\n",
       "      <td>&lt; subdivision &lt;</td>\n",
       "      <td>Nywening</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>864833</th>\n",
       "      <td>Anthyllis</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Anthyllis splendens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1209316</th>\n",
       "      <td>Psilochilus</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Psilochilus vallecaucanus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228388</th>\n",
       "      <td>Sumner County, Kansas</td>\n",
       "      <td>&lt; subdivision &lt;</td>\n",
       "      <td>Cicero</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1671191</th>\n",
       "      <td>Tethya</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Tethya irisae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>288516</th>\n",
       "      <td>Eaton County, Michigan</td>\n",
       "      <td>&gt; largestCity &gt;</td>\n",
       "      <td>Eaton Rapids</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>287348</th>\n",
       "      <td>Boone County, Missouri</td>\n",
       "      <td>&gt; largestCity &gt;</td>\n",
       "      <td>Ashland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1758229</th>\n",
       "      <td>Ormiscus</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Ormiscus vulgaris</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1748675</th>\n",
       "      <td>Sphecodes</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Sphecodes mutillaeformis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1787612</th>\n",
       "      <td>Silis (beetle)</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Silis parallela</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1157946</th>\n",
       "      <td>Diplopterygium</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Diplopterygium conversum</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>841225</th>\n",
       "      <td>Agrimonia</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Agrimonia parviflora</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1945864</th>\n",
       "      <td>Dermestes</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Dermestes patagoniensis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1197572</th>\n",
       "      <td>Tamolanica</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Tamolanica katauana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>268117</th>\n",
       "      <td>Tupelo micropolitan area</td>\n",
       "      <td>&lt; subdivision &lt;</td>\n",
       "      <td>Tupelo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147551</th>\n",
       "      <td>Promachus (fly)</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Promachus neligens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179891</th>\n",
       "      <td>Zonaria</td>\n",
       "      <td>&gt; bandMember &gt;</td>\n",
       "      <td>Rickard Lundmark</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1699982</th>\n",
       "      <td>Melanorivulus</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Melanorivulus amambaiensis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>816105</th>\n",
       "      <td>Bacillus</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>B. haloalkaliphilus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1219087</th>\n",
       "      <td>Bubastes</td>\n",
       "      <td>&lt; genus &lt;</td>\n",
       "      <td>Bubastes blackburni</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           target              rel                      E_text\n",
       "274906            Sturgeon County  < subdivision <                    Nywening\n",
       "864833                  Anthyllis        < genus <         Anthyllis splendens\n",
       "1209316               Psilochilus        < genus <   Psilochilus vallecaucanus\n",
       "228388      Sumner County, Kansas  < subdivision <                      Cicero\n",
       "1671191                    Tethya        < genus <               Tethya irisae\n",
       "288516     Eaton County, Michigan  > largestCity >                Eaton Rapids\n",
       "287348     Boone County, Missouri  > largestCity >                     Ashland\n",
       "1758229                  Ormiscus        < genus <           Ormiscus vulgaris\n",
       "1748675                 Sphecodes        < genus <    Sphecodes mutillaeformis\n",
       "1787612            Silis (beetle)        < genus <             Silis parallela\n",
       "1157946            Diplopterygium        < genus <    Diplopterygium conversum\n",
       "841225                  Agrimonia        < genus <        Agrimonia parviflora\n",
       "1945864                 Dermestes        < genus <     Dermestes patagoniensis\n",
       "1197572                Tamolanica        < genus <         Tamolanica katauana\n",
       "268117   Tupelo micropolitan area  < subdivision <                      Tupelo\n",
       "147551            Promachus (fly)        < genus <          Promachus neligens\n",
       "179891                    Zonaria   > bandMember >            Rickard Lundmark\n",
       "1699982             Melanorivulus        < genus <  Melanorivulus amambaiensis\n",
       "816105                   Bacillus        < genus <         B. haloalkaliphilus\n",
       "1219087                  Bubastes        < genus <         Bubastes blackburni"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new_relations.sample(20)[['target', 'rel', 'E_text']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# write new relations to file\n",
    "\n",
    "def serialize_relations(df, filename):\n",
    "    triples = []\n",
    "    for _, r in df.iterrows():\n",
    "        s, p, o = clg_util.name2clg_resource(r['target']), r['pred'].replace('dbpedia', 'caligraph'), clg_util.name2clg_resource(r['E_ent'])\n",
    "        if r['inv']:\n",
    "            s, o = o, s\n",
    "        triples.append(serialize_util.as_object_triple(s, p, o))\n",
    "    with open(filename, mode='w') as f:\n",
    "        f.writelines(triples)\n",
    "        \n",
    "serialize_relations(df_new_relations, 'new_relations.nt')"
   ]
  }
 ],
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