OpenNLP 2.5.12.
Usage: opennlp TOOL
where TOOL is one of:

  Doccat                            Learned 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 20newsgroup data format to native OpenNLP format
  LanguageDetector                  Learned language detector
  LanguageDetectorTrainer           Trainer for the learnable language detector
  LanguageDetectorConverter         Converts leipzig data format to native OpenNLP format
  LanguageDetectorCrossValidator    K-fold cross validator for the learnable Language Detector
  LanguageDetectorEvaluator         Measures the performance of the Language Detector model with the reference data
  DictionaryBuilder                 Builds a new dictionary
  SimpleTokenizer                   Character class tokenizer
  TokenizerME                       Learnable tokenizer
  TokenizerTrainer                  Trainer for the learnable tokenizer
  TokenizerMEEvaluator              Measures the performance of the learnable tokenizer
  TokenizerCrossValidator           K-fold cross validator for the learnable tokenizer
  TokenizerConverter                Converts external data formats (irishsentencebank,ad,pos,masc,conllx,namefinder,parse,conllu) to native OpenNLP format
  DictionaryDetokenizer             Normalizes tokenized text according to rules defined in a detokenizer dictionary
  SentenceDetector                  Learnable sentence detector
  SentenceDetectorTrainer           Trainer for the learnable sentence detector
  SentenceDetectorEvaluator         Measures the performance of the learnable sentence detector
  SentenceDetectorCrossValidator    K-fold cross validator for the learnable sentence detector
  SentenceDetectorConverter         Converts external data formats (nkjp,irishsentencebank,ad,pos,masc,conllx,namefinder,parse,moses,conllu,letsmt) 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 external data formats (evalita,ad,conll03,bionlp2004,conll02,masc,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 external data formats (ad,masc,conllx,parse,ontonotes,conllu) to native OpenNLP format
  LemmatizerME                      Learnable lemmatizer
  LemmatizerTrainerME               Trainer for the learnable lemmatizer
  LemmatizerEvaluator               Measures the performance of the Lemmatizer model with the reference data
  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 external 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
  NGramLanguageModel                Gives the probability and most probable next token(s) of a sequence of tokens in a language model

All tools print help when invoked with help parameter
Example: opennlp SimpleTokenizer help

cd /opt/opennlp-2.5.12 && ./bin/opennlp
ls -lh /opt/opennlp/models/

-rw-r--r-- 1 root root 5.0M en-ner-person.bin
-rw-r--r-- 1 root root  97K en-sent.bin
-rw-r--r-- 1 root root 430K en-token.bin
-rw-r--r-- 1 root root 509K opennlp-en-ud-ewt-lemmas-1.3-2.5.4.bin
-rw-r--r-- 1 root root 1.2M opennlp-en-ud-ewt-pos-1.3-2.5.4.bin
-rw-r--r-- 1 root root  20K opennlp-en-ud-ewt-sentence-1.3-2.5.4.bin
-rw-r--r-- 1 root root 319K opennlp-en-ud-ewt-tokens-1.3-2.5.4.bin
-rw-r--r-- 1 root root 141K langdetect-183.bin

Usage: opennlp SimpleTokenizer < sentences
Usage: opennlp TokenizerME model < sentences
Usage: opennlp SentenceDetector model < sentences
Usage: opennlp POSTagger model < sentences
Usage: opennlp TokenNameFinder model1 model2 ... modelN < sentences
Usage: opennlp LemmatizerME model < sentences
Usage: opennlp Doccat model < documents
Usage: opennlp LanguageDetector model < documents

cd /opt/opennlp-2.5.12
printf "Pierre Vinken, 61 years old, will join the board as a nonexecutive director on November 29. Mr. Vinken is chairman of Elsevier N.V., the Dutch publishing group.\n" | ./bin/opennlp SimpleTokenizer

Pierre Vinken , 61 years old , will join the board as a nonexecutive director on November 29 . Mr . Vinken is chairman of Elsevier N . V . , the Dutch publishing group .
Average: 111.1 sent/s

Total: 1 sent
Runtime: 0.009s
Execution time: 0.030 seconds

cd /opt/opennlp-2.5.12
printf "Pierre Vinken, 61 years old, will join the board as a nonexecutive director on November 29. Mr. Vinken is chairman of Elsevier N.V., the Dutch publishing group.\n" | ./bin/opennlp TokenizerME /opt/opennlp/models/en-token.bin

Loading Tokenizer model ...
done (0.151s)

Pierre Vinken , 61 years old , will join the board as a nonexecutive director on November 29 . Mr. Vinken is chairman of Elsevier N.V. , the Dutch publishing group .
Average: 100.0 sent/s

Total: 1 sent
Runtime: 0.01s
Execution time: 0.179 seconds

cd /opt/opennlp-2.5.12
printf "Pierre Vinken, 61 years old, will join the board as a nonexecutive director on November 29. Mr. Vinken is chairman of Elsevier N.V., the Dutch publishing group.\n" | ./bin/opennlp SentenceDetector /opt/opennlp/models/en-sent.bin

Loading Sentence Detector model ...
done (0.066s)

Pierre Vinken, 61 years old, will join the board as a nonexecutive director on November 29.
Mr. Vinken is chairman of Elsevier N.V., the Dutch publishing group.
Average: 500.0 sent/s

Total: 2 sent
Runtime: 0.004s
Execution time: 0.086 seconds

cd /opt/opennlp-2.5.12
printf "Pierre Vinken, 61 years old, will join the board as a nonexecutive director on November 29. Mr. Vinken is chairman of Elsevier N.V., the Dutch publishing group.\n" | ./bin/opennlp POSTagger /opt/opennlp/models/opennlp-en-ud-ewt-pos-1.3-2.5.4.bin

Loading POS Tagger model ...
done (0.266s)

Pierre_PROPN Vinken,_PROPN 61_NUM years_NOUN old,_PUNCT will_AUX join_VERB the_DET board_NOUN as_ADP a_DET nonexecutive_ADJ director_NOUN on_ADP November_PROPN 29._PUNCT Mr._PROPN Vinken_PROPN is_AUX chairman_NOUN of_ADP Elsevier_ADJ N.V.,_PROPN the_DET Dutch_PROPN publishing_VERB group._PUNCT
Average: 21.3 sent/s

Total: 1 sent
Runtime: 0.047s
Execution time: 0.365 seconds

cd /opt/opennlp-2.5.12
printf "Pierre Vinken is the chairman of Elsevier N.V. He was born in Amsterdam in 1931. Alice Smith works at Google in New York.\n" | ./bin/opennlp TokenNameFinder /opt/opennlp/models/en-ner-person.bin

Loading Token Name Finder model ...
done (0.639s)

<START:person> Pierre Vinken <END> is the chairman of Elsevier N.V. He was born in Amsterdam in 1931. Alice Smith works at Google in New York.
Average: 17.5 sent/s

Total: 1 sent
Runtime: 0.057s
Execution time: 0.750 seconds

cd /opt/opennlp-2.5.12
printf "The_DET dogs_NOUN are_AUX running_VERB quickly_ADV through_ADP the_DET fields_NOUN ._PUNCT\n" | ./bin/opennlp LemmatizerME /opt/opennlp/models/opennlp-en-ud-ewt-lemmas-1.3-2.5.4.bin

Loading Lemmatizer model ...
done (0.144s)

The     DET     the
dogs    NOUN    dog
are     AUX     be
running VERB    run
quickly ADV     quickly
through ADP     through
the     DET     the
fields  NOUN    field
.       PUNCT   .

Average: 62.5 sent/s

Total: 1 sent
Runtime: 0.016s
Execution time: 0.176 seconds

cd /opt/opennlp-2.5.12
printf "This is an English sentence.\n" | ./bin/opennlp LanguageDetector /opt/opennlp/models/langdetect-183.bin

Loading Language Detector model ...
done (0.683s)

eng     This is an English sentence.

Average: 62.5 doc/s

Total: 1 doc
Runtime: 0.016s
Execution time: 0.726 seconds

This<SPLIT>is<SPLIT>a<SPLIT>sample<SPLIT>sentence<SPLIT>for<SPLIT>tokenizer<SPLIT>training<SPLIT>.

cd /opt/opennlp-2.5.12
./bin/opennlp TokenizerTrainer -lang en -cutoff 1 -iterations 100 -model /opt/opennlp/models/en-token-custom.bin -data /opt/opennlp/train/en-token-sample.train -encoding UTF-8

Indexing events with TwoPass using cutoff of 1
Computing event counts...
done. 9504 events
Indexing...
done.
Sorting and merging events...
done. Reduced 9504 events to 792.
Done indexing in 0.36 s.
Incorporating indexed data for training...
done.
        Number of Event Tokens: 792
         Number of Outcomes: 2
         Number of Predicates: 2461
...done.
Computing model parameters ...
Performing 100 iterations.
1: (7716/9504) Log Likelihood : -6587.670804041749
2: (7836/9504) Log Likelihood : -4108.5332447883475
...
100: (9504/9504) Log Likelihood : -176.4261324887696
Training finished after completing 100 iterations successfully.
Writing tokenizer model ...
done (0.083s)

Wrote tokenizer model to path: /opt/opennlp/models/en-token-custom.bin
Execution time: 0.807 seconds

cd /opt/opennlp-2.5.12
printf "This is a sample sentence for the custom trained tokenizer model.\n" | ./bin/opennlp TokenizerME /opt/opennlp/models/en-token-custom.bin

Loading Tokenizer model ...
done (0.051s)

This is a sample sentence for the cus tom trained tokenizer model .
Average: 47.6 sent/s

Total: 1 sent
Runtime: 0.021s
Execution time: 0.111 seconds

Usage: opennlp POSTaggerTrainer[.ad|.masc|.conllx|.parse|.ontonotes|.conllu] [-factory factoryName] [-resources resourcesDir] [-featuregen featuregenFile] [-dict dictionaryPath] [-tagDictCutoff tagDictCutoff] [-params paramsFile] -lang language -model modelFile -data sampleData [-encoding charsetName]

Usage: opennlp TokenNameFinderTrainer[.evalita|.ad|.conll03|.bionlp2004|.conll02|.masc|.muc6|.ontonotes|.brat] [-factory factoryName] [-resources resourcesDir] [-type modelType] [-featuregen featuregenFile] [-nameTypes types] [-sequenceCodec codec] [-params paramsFile] -lang language -model modelFile -data sampleData [-encoding charsetName]

Usage: opennlp SentenceDetectorTrainer[.nkjp|.irishsentencebank|.ad|.pos|.masc|.conllx|.namefinder|.parse|.moses|.conllu|.letsmt] [-factory factoryName] [-abbDict path] [-eosChars string] [-useTokenEnd useTokenEnd] [-params paramsFile] -lang language -model modelFile -data sampleData [-encoding charsetName]

Usage: opennlp DoccatTrainer[.20newsgroup] [-factory factoryName] [-featureGenerators fg] [-params paramsFile] -lang language -model modelFile -data sampleData [-encoding charsetName]

import opennlp.tools.tokenize.TokenizerModel;
import opennlp.tools.tokenize.TokenizerME;

TokenizerModel model = new TokenizerModel(new FileInputStream("/opt/opennlp/models/en-token.bin"));
TokenizerME tokenizer = new TokenizerME(model);
String[] tokens = tokenizer.tokenize("Pierre Vinken, 61 years old.");

import opennlp.tools.postag.POSModel;
import opennlp.tools.postag.POSTaggerME;

POSModel model = new POSModel(new FileInputStream("/opt/opennlp/models/opennlp-en-ud-ewt-pos-1.3-2.5.4.bin"));
POSTaggerME tagger = new POSTaggerME(model);
String[] tags = tagger.tag(tokens);   // tokens 来自分词器，与输出一一对应

import opennlp.tools.namefind.TokenNameFinderModel;
import opennlp.tools.namefind.NameFinderME;
import opennlp.tools.util.Span;

TokenNameFinderModel model = new TokenNameFinderModel(new FileInputStream("/opt/opennlp/models/en-ner-person.bin"));
NameFinderME finder = new NameFinderME(model);
Span[] spans = finder.find(tokens);
double[] probs = finder.probs(spans);
for (int i = 0; i < spans.length; i++) {
    Span span = spans[i];
    System.out.println("类型=" + span.getType() + " 概率=" + probs[i] + " 实体="
            + String.join(" ", Arrays.copyOfRange(tokens, span.getStart(), span.getEnd())));
}