This is a tool meant for tagging words with their part-of-speech, a grammatical category based on their function within a sentence, such as noun, adjective, verb, and so forth.
You can also see Python, Cython, C++, C, Swift, Js, or C# repository.
- Java Development Kit 8 or higher, Open JDK or Oracle JDK
- Maven
- Git
To check if you have a compatible version of Java installed, use the following command:
java -version
If you don't have a compatible version, you can download either Oracle JDK or OpenJDK
To check if you have Maven installed, use the following command:
mvn --version
To install Maven, you can follow the instructions here.
Install the latest version of Git.
In order to work on code, create a fork from GitHub page. Use Git for cloning the code to your local or below line for Ubuntu:
git clone <your-fork-git-link>
A directory called PosTagger will be created. Or you can use below link for exploring the code:
git clone https://github.com/olcaytaner/PosTagger.git
Steps for opening the cloned project:
- Start IDE
- Select File | Open from main menu
- Choose
PosTagger/pom.xmlfile - Select open as project option
- Couple of seconds, dependencies with Maven will be downloaded.
From IDE
After being done with the downloading and Maven indexing, select Build Project option from Build menu. After compilation process, user can run PosTagger.
From Console
Go to PosTagger directory and compile with
mvn compile
From IDE
Use package of 'Lifecycle' from maven window on the right and from PosTagger root module.
From Console
Use below line to generate jar file:
mvn install
<dependency>
<groupId>io.github.starlangsoftware</groupId>
<artifactId>PosTagger</artifactId>
<version>1.0.3</version>
</dependency>
To train the PosTagger which is used for English pos tagging
void train(PosTaggedCorpus corpus)
To save the trained PosTagger model
void saveModel()
To load an already trained PosTagger model
void loadModel()
To tag a sentence, using a newly trained or loaded PosTagger model
Sentence posTag(Sentence sentence)
3 different PosTagger models are supported: The one that is used to tag the sentences with a random tag
DummyPosTagger
the one that tags the word with the most used tag for a given word
NaivePosTagger
the one that does an Hmm based training and tags the words accordingly
HmmPosTagger