Stanford NLP Parser PHP wrapper in Docker

About Stanford Parser (https://nlp.stanford.edu/software/lex-parser.html)

A natural language parser is a program that works out the grammatical structure of sentences, for instance, which groups of words go together (as "phrases") and which words are the subject or object of a verb. Probabilistic parsers use knowledge of language gained from hand-parsed sentences to try to produce the most likely analysis of new sentences. These statistical parsers still make some mistakes, but commonly work rather well. Their development was one of the biggest breakthroughs in natural language processing in the 1990s.

Run on your machine

docker build -t alen-z/php-stanford-nlp-docker https://github.com/alen-z/php-stanford-nlp-docker.git
docker run --name nlp -p 8000:80 alen-z/php-stanford-nlp-docker

Get Docker container shell while running:

docker exec -it nlp bash

Start closed Docker container:

docker start nlp

Usage

Parse ONE sentence

Go to 0.0.0.0:8000/?q=Dogs are the best! to get:

{
    "wordsAndTags": [
        [
            "Dogs",
            "NNS"
        ],
        [
            "are",
            "VBP"
        ],
        [
            "the",
            "DT"
        ],
        [
            "best",
            "JJS"
        ],
        [
            "!",
            "."
        ]
    ],
    "penn": {
        "parent": "ROOT",
        "children": [
            {
                "parent": "S",
                "children": [
                    {
                        "parent": "NP",
                        "children": [
                            {
                                "parent": "NNS Dogs",
                                "children": []
                            }
                        ]
                    },
                    {
                        "parent": "VP",
                        "children": [
                            {
                                "parent": "VBP are",
                                "children": []
                            },
                            {
                                "parent": "NP",
                                "children": [
                                    {
                                        "parent": "DT the",
                                        "children": []
                                    },
                                    {
                                        "parent": "JJS best",
                                        "children": []
                                    }
                                ]
                            }
                        ]
                    },
                    {
                        "parent": ". !",
                        "children": []
                    }
                ]
            }
        ]
    },
    "typedDependencies": [
        {
            "type": "nsubj",
            "0": {
                "feature": "best",
                "index": 4
            },
            "1": {
                "feature": "Dogs",
                "index": 1
            }
        },
        {
            "type": "cop",
            "0": {
                "feature": "best",
                "index": 4
            },
            "1": {
                "feature": "are",
                "index": 2
            }
        },
        {
            "type": "det",
            "0": {
                "feature": "best",
                "index": 4
            },
            "1": {
                "feature": "the",
                "index": 3
            }
        },
        {
            "type": "root",
            "0": {
                "feature": "ROOT",
                "index": 0
            },
            "1": {
                "feature": "best",
                "index": 4
            }
        }
    ],
    "legend": {
        "NNS": "noun, plural",
        "VBP": "verb, non-3rd person singular present",
        "DT": "determiner",
        "JJS": "adjective, superlative",
        ".": "punctuation mark, sentence closer",
        "NP": "noun phrase",
        "VP": "verb phrase",
        "nsubj": "nominal subject",
        "cop": "copula",
        "det": "determiner",
        "root": "root"
    },
    "query": "Dogs are the best!"
}

Get raw Stanford Parser output for one or multiple sentences

Use additional raw=true parameter. Go to 0.0.0.0:8000/?q=Dogs rock! OK, cats are also...fine.&raw=true to get:

Dogs/NNS rock/NN !/.

(ROOT
  (NP
    (NP (NNS Dogs))
    (NP (NN rock))
    (. !)))

root(ROOT-0, Dogs-1)
dep(Dogs-1, rock-2)

OK/UH ,/, cats/NNS are/VBP also/RB .../: fine/NN ./.

(ROOT
  (S
    (INTJ (UH OK))
    (, ,)
    (NP (NNS cats))
    (VP (VBP are)
      (ADVP (RB also))
      (: ...)
      (NP (NN fine)))
    (. .)))

discourse(fine-7, OK-1)
nsubj(fine-7, cats-3)
cop(fine-7, are-4)
advmod(fine-7, also-5)
root(ROOT-0, fine-7)

Tips

If you want to use special characters like & in your sentence encode the input. For example 'cat & mouse' should be cat%20%26%20mouse.