Project

open_nlp

0.01
No commit activity in last 3 years
No release in over 3 years
JRuby tools wrapper for Apache OpenNLP
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
 Dependencies
 Project Readme

OpenNlp

Build Status Code Climate

A JRuby wrapper for the Apache OpenNLP tools library, that allows you execute common natural language processing tasks, such as

  • sentence detection
  • tokenize
  • part-of-speech tagging
  • named entity extraction
  • chunks detection
  • parsing
  • document categorization

Installation

Add this line to your application's Gemfile:

gem 'open_nlp'

And then execute:

$ bundle

Or install it yourself as:

$ gem install open_nlp

Usage

To use open_nlp classes, you need to require it in your sources

require 'open_nlp'

Then you can create instances of open_nlp classes and use it for your nlp tasks

Sentence detection

sentence_detect_model = OpenNlp::Model::SentenceDetector.new("nlp_models/en-sent.bin")
sentence_detector = OpenNlp::SentenceDetector.new(sentence_detect_model)

# get sentences as array of strings
sentence_detector.detect('The red fox sleeps soundly.')

# get array of OpenNLP::Util::Span objects:
sentence_detector.pos_detect('"The sky is blue. The Grass is green."')

Tokenize

token_model = OpenNlp::Model::Tokenizer.new("nlp_models/en-token.bin")
tokenizer = OpenNlp::Tokenizer.new(token_model)
tokenizer.tokenize('The red fox sleeps soundly.')

Part-of-speech tagging

pos_model = OpenNlp::Model::POSTagger.new(File.join("nlp_models/en-pos-maxent.bin"))
pos_tagger = OpenNlp::POSTagger.new(pos_model)

# to tag string call OpenNlp::POSTagger#tag with String argument
pos_tagger.tag('The red fox sleeps soundly.')

# to tag array of tokens call OpenNlp::POSTagger#tag with Array argument
pos_tagger.tag(%w|The red fox sleeps soundly .|)

Chunks detection

# chunker also needs tokenizer and pos-tagger models
# because it uses tokenizing and pos-tagging inside chunk task
chunk_model = OpenNlp::Model::Chunker.new(File.join("nlp_models/en-chunker.bin"))
token_model = OpenNlp::Model::Tokenizer.new("nlp_models/en-token.bin")
pos_model = OpenNlp::Model::POSTagger.new(File.join("nlp_models/en-pos-maxent.bin"))
chunker = OpenNlp::Chunker.new(chunk_model, token_model, pos_model)
chunker.chunk('The red fox sleeps soundly.')

Parsing

# parser also needs tokenizer model because it uses tokenizer inside parse task
parse_model = OpenNlp::Model::Parser.new(File.join("nlp_models/en-parser-chunking.bin"))
token_model = OpenNlp::Model::Tokenizer.new("nlp_models/en-token.bin")
parser = OpenNlp::Parser.new(parse_model, token_model)

# the result will be an instance of OpenNlp::Parser::Parse
parse_info = parser.parse('The red fox sleeps soundly.')

# you can get tree bank string by calling
parse_info.tree_bank_string

# you can get code tree structure of parse result by calling
parse_info.code_tree

Categorizing

doccat_model = OpenNlp::Model::Parser.new(File.join("nlp_models/en-doccat.bin"))
categorizer = OpenNlp::Categorizer.new(doccat_model)
categorizer.categorize("Quick brown fox jumps very bad.")

Contributing

  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Add some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create new Pull Request