Prerequisite
OpenNLP
requires Java. Install Java and make sure you set JAVA_HOME.
Step 1: Download OpenNLP binaries from following link.
Step 2: Extract the tar file. Set the variable ‘OPENNLP_HOME’
to root directory of OpenNLP.
I set like
below.
export
OPENNLP_HOME=/Users/harikrishna_gurram/OpenNLP/apache-opennlp-1.6.0
Add ‘$OPENNLP_HOME/bin’
to your system path. If you are using windows add ‘%OPENNLP_HOME%\bin’ to your
system path.
Step 3: Open new terminal and type ‘opennlp’. You will get
following kind of output.
$ opennlp OpenNLP 1.6.0. Usage: opennlp TOOL where TOOL is one of: Doccat learnable document categorizer DoccatTrainer trainer for the learnable document categorizer DoccatEvaluator Measures the performance of the Doccat model with the reference data DoccatCrossValidator K-fold cross validator for the learnable Document Categorizer DoccatConverter converts leipzig data format to native OpenNLP format DictionaryBuilder builds a new dictionary SimpleTokenizer character class tokenizer TokenizerME learnable tokenizer TokenizerTrainer trainer for the learnable tokenizer TokenizerMEEvaluator evaluator for the learnable tokenizer TokenizerCrossValidator K-fold cross validator for the learnable tokenizer TokenizerConverter converts foreign data formats (ad,pos,conllx,namefinder,parse) to native OpenNLP format DictionaryDetokenizer SentenceDetector learnable sentence detector SentenceDetectorTrainer trainer for the learnable sentence detector SentenceDetectorEvaluator evaluator for the learnable sentence detector SentenceDetectorCrossValidator K-fold cross validator for the learnable sentence detector SentenceDetectorConverter converts foreign data formats (ad,pos,conllx,namefinder,parse) to native OpenNLP format TokenNameFinder learnable name finder TokenNameFinderTrainer trainer for the learnable name finder TokenNameFinderEvaluator Measures the performance of the NameFinder model with the reference data TokenNameFinderCrossValidator K-fold cross validator for the learnable Name Finder TokenNameFinderConverter converts foreign data formats (evalita,ad,conll03,bionlp2004,conll02,muc6,ontonotes,brat) to native OpenNLP format CensusDictionaryCreator Converts 1990 US Census names into a dictionary POSTagger learnable part of speech tagger POSTaggerTrainer trains a model for the part-of-speech tagger POSTaggerEvaluator Measures the performance of the POS tagger model with the reference data POSTaggerCrossValidator K-fold cross validator for the learnable POS tagger POSTaggerConverter converts foreign data formats (ad,conllx,parse,ontonotes) to native OpenNLP format ChunkerME learnable chunker ChunkerTrainerME trainer for the learnable chunker ChunkerEvaluator Measures the performance of the Chunker model with the reference data ChunkerCrossValidator K-fold cross validator for the chunker ChunkerConverter converts ad data format to native OpenNLP format Parser performs full syntactic parsing ParserTrainer trains the learnable parser ParserEvaluator Measures the performance of the Parser model with the reference data ParserConverter converts foreign data formats (ontonotes,frenchtreebank) to native OpenNLP format BuildModelUpdater trains and updates the build model in a parser model CheckModelUpdater trains and updates the check model in a parser model TaggerModelReplacer replaces the tagger model in a parser model EntityLinker links an entity to an external data set All tools print help when invoked with help parameter Example: opennlp SimpleTokenizer help
To get help
for any opennlp tool, just type the command ‘opennlp toolname’.
To get help
for ‘parser’ tool, type ‘opennlp Parser’.
$ opennlp Parser Usage: opennlp Parser [-bs n -ap n -k n] model < sentences -bs n: Use a beam size of n. -ap f: Advance outcomes in with at least f% of the probability mass. -k n: Show the top n parses. This will also display their log-probablities.
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