Apache OpenNLP
OpenNLP provides a Java API for NLP tasks including tokenization, sentence detection, POS tagging, named entity recognition, chunking, parsing, and language detection, with support for training custom models.
OpenAPI Specification
openapi: 3.0.3
info:
title: Apache OpenNLP Tools API
description: Apache OpenNLP is a machine learning based toolkit for processing natural language text, supporting tokenization, sentence segmentation, POS tagging, named entity extraction, chunking, parsing, and coreference resolution. This API represents the REST-accessible surface of the OpenNLP toolkit.
version: 2.5.8
license:
name: Apache 2.0
url: https://www.apache.org/licenses/LICENSE-2.0
contact:
url: https://opennlp.apache.org/
x-generated-from: documentation
servers:
- url: https://{host}/opennlp
description: Apache OpenNLP REST service
variables:
host:
default: localhost:8080
paths:
/detect/language:
post:
operationId: detectLanguage
summary: Apache OpenNLP Detect Language
description: Detect the language of the provided text using the language detector model.
tags: [Language Detection]
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/TextRequest'
responses:
'200':
description: Language detection result
content:
application/json:
schema:
$ref: '#/components/schemas/LanguageDetectionResult'
x-microcks-operation:
delay: 0
dispatcher: FALLBACK
/detect/sentences:
post:
operationId: detectSentences
summary: Apache OpenNLP Detect Sentences
description: Split input text into individual sentences using the sentence detector model.
tags: [Sentence Detection]
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/TextRequest'
responses:
'200':
description: Sentence detection result
content:
application/json:
schema:
$ref: '#/components/schemas/SentenceDetectionResult'
x-microcks-operation:
delay: 0
dispatcher: FALLBACK
/tokenize:
post:
operationId: tokenize
summary: Apache OpenNLP Tokenize Text
description: Segment input text into individual tokens (words, punctuation) using the tokenizer model.
tags: [Tokenization]
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/TextRequest'
responses:
'200':
description: Tokenization result
content:
application/json:
schema:
$ref: '#/components/schemas/TokenizationResult'
x-microcks-operation:
delay: 0
dispatcher: FALLBACK
/ner:
post:
operationId: findNamedEntities
summary: Apache OpenNLP Find Named Entities
description: Detect and classify named entities (persons, locations, organizations, dates) in tokenized text.
tags: [Named Entity Recognition]
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/TokensRequest'
responses:
'200':
description: Named entity recognition result
content:
application/json:
schema:
$ref: '#/components/schemas/NERResult'
x-microcks-operation:
delay: 0
dispatcher: FALLBACK
/pos/tag:
post:
operationId: tagPartsOfSpeech
summary: Apache OpenNLP Tag Parts of Speech
description: Assign POS tags (noun, verb, adjective, etc.) to each token in the tokenized text.
tags: [POS Tagging]
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/TokensRequest'
responses:
'200':
description: POS tagging result
content:
application/json:
schema:
$ref: '#/components/schemas/POSTaggingResult'
x-microcks-operation:
delay: 0
dispatcher: FALLBACK
/lemmatize:
post:
operationId: lemmatize
summary: Apache OpenNLP Lemmatize Text
description: Reduce tokens to their base/lemma forms using POS context.
tags: [Lemmatization]
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/POSTokensRequest'
responses:
'200':
description: Lemmatization result
content:
application/json:
schema:
$ref: '#/components/schemas/LemmatizationResult'
x-microcks-operation:
delay: 0
dispatcher: FALLBACK
/chunk:
post:
operationId: chunkText
summary: Apache OpenNLP Chunk Text
description: Identify shallow syntactic phrases (noun phrases, verb phrases) in tokenized text with POS tags.
tags: [Chunking]
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/POSTokensRequest'
responses:
'200':
description: Chunking result
content:
application/json:
schema:
$ref: '#/components/schemas/ChunkingResult'
x-microcks-operation:
delay: 0
dispatcher: FALLBACK
/parse:
post:
operationId: parseText
summary: Apache OpenNLP Parse Text
description: Perform full syntactic parsing to build a parse tree for a sentence.
tags: [Parsing]
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/TextRequest'
responses:
'200':
description: Parse tree result
content:
application/json:
schema:
$ref: '#/components/schemas/ParseResult'
x-microcks-operation:
delay: 0
dispatcher: FALLBACK
/categorize:
post:
operationId: categorizeDocument
summary: Apache OpenNLP Categorize Document
description: Classify a document into predefined categories using the document categorizer model.
tags: [Document Categorization]
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/TextRequest'
responses:
'200':
description: Document categorization result
content:
application/json:
schema:
$ref: '#/components/schemas/CategorizationResult'
x-microcks-operation:
delay: 0
dispatcher: FALLBACK
/models:
get:
operationId: listModels
summary: Apache OpenNLP List Available Models
description: List all available NLP models loaded in the OpenNLP service.
tags: [Models]
responses:
'200':
description: List of available models
content:
application/json:
schema:
$ref: '#/components/schemas/ModelList'
x-microcks-operation:
delay: 0
dispatcher: FALLBACK
/models/{modelId}:
get:
operationId: getModel
summary: Apache OpenNLP Get Model
description: Get metadata about a specific NLP model.
tags: [Models]
parameters:
- name: modelId
in: path
required: true
description: Unique model identifier
schema:
type: string
example: en-ner-person.bin
responses:
'200':
description: Model metadata
content:
application/json:
schema:
$ref: '#/components/schemas/ModelInfo'
'404':
description: Model not found
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
x-microcks-operation:
delay: 0
dispatcher: FALLBACK
components:
schemas:
TextRequest:
type: object
required: [text]
properties:
text:
type: string
description: Input text to process
example: Pierre Vinken, 61 years old, will join the board as a nonexecutive director Nov. 29.
language:
type: string
description: ISO-639-3 language code hint
example: eng
modelId:
type: string
description: Specific model to use (optional)
example: en-sent.bin
TokensRequest:
type: object
required: [tokens]
properties:
tokens:
type: array
items:
type: string
description: Pre-tokenized array of text tokens
example: ["Pierre", "Vinken", "will", "join", "the", "board"]
language:
type: string
description: ISO-639-3 language code
example: eng
POSTokensRequest:
type: object
required: [tokens, posTags]
properties:
tokens:
type: array
items:
type: string
description: Pre-tokenized array of text tokens
example: ["Pierre", "Vinken", "will", "join"]
posTags:
type: array
items:
type: string
description: POS tags for each token
example: ["NNP", "NNP", "MD", "VB"]
LanguageDetectionResult:
type: object
properties:
bestLanguage:
type: string
description: ISO-639-3 code of most likely language
example: eng
confidence:
type: number
description: Confidence score 0-1
example: 0.98
languages:
type: array
description: All detected languages with probabilities
items:
$ref: '#/components/schemas/LanguageProbability'
LanguageProbability:
type: object
properties:
language:
type: string
description: ISO-639-3 language code
example: eng
probability:
type: number
description: Probability score
example: 0.98
SentenceDetectionResult:
type: object
properties:
sentences:
type: array
items:
type: string
description: Detected sentences
example: ["Pierre Vinken will join the board.", "He is 61 years old."]
spans:
type: array
items:
$ref: '#/components/schemas/Span'
TokenizationResult:
type: object
properties:
tokens:
type: array
items:
type: string
description: Extracted tokens
example: ["Pierre", "Vinken", ",", "61", "years", "old"]
spans:
type: array
items:
$ref: '#/components/schemas/Span'
probabilities:
type: array
items:
type: number
description: Confidence for each token boundary
NERResult:
type: object
properties:
entities:
type: array
items:
$ref: '#/components/schemas/NamedEntity'
NamedEntity:
type: object
properties:
text:
type: string
description: Entity text
example: Pierre Vinken
type:
type: string
description: Entity type
example: person
enum: [person, location, organization, date, time, money, percent, misc]
start:
type: integer
description: Start token index
example: 0
end:
type: integer
description: End token index (exclusive)
example: 2
probability:
type: number
description: Confidence score
example: 0.95
POSTaggingResult:
type: object
properties:
tokens:
type: array
items:
type: string
example: ["Pierre", "Vinken", "will", "join"]
tags:
type: array
items:
type: string
description: POS tags (Penn Treebank tagset)
example: ["NNP", "NNP", "MD", "VB"]
probabilities:
type: array
items:
type: number
LemmatizationResult:
type: object
properties:
tokens:
type: array
items:
type: string
example: ["running", "faster"]
lemmas:
type: array
items:
type: string
example: ["run", "fast"]
ChunkingResult:
type: object
properties:
chunks:
type: array
items:
$ref: '#/components/schemas/Chunk'
Chunk:
type: object
properties:
text:
type: string
description: Chunk text
example: Pierre Vinken
type:
type: string
description: Chunk type
example: NP
enum: [NP, VP, PP, ADJP, ADVP, SBAR, PRT, CONJP, INTJ, LST, UCP]
start:
type: integer
example: 0
end:
type: integer
example: 2
ParseResult:
type: object
properties:
parseTree:
type: string
description: Penn Treebank-style parse tree
example: "(S (NP Pierre Vinken) (VP will join (NP the board)))"
probability:
type: number
description: Parse probability
example: 0.87
CategorizationResult:
type: object
properties:
bestCategory:
type: string
description: Most likely category label
example: Sports
probabilities:
type: object
additionalProperties:
type: number
description: Probability for each category
ModelList:
type: object
properties:
models:
type: array
items:
$ref: '#/components/schemas/ModelInfo'
ModelInfo:
type: object
properties:
modelId:
type: string
description: Unique model identifier
example: en-ner-person.bin
language:
type: string
description: Model language
example: eng
type:
type: string
description: Model type
example: TokenNameFinder
version:
type: string
description: Model version
example: 1.5
loaded:
type: boolean
description: Whether model is currently loaded
example: true
Span:
type: object
properties:
start:
type: integer
description: Start character offset
example: 0
end:
type: integer
description: End character offset (exclusive)
example: 13
type:
type: string
description: Span type if applicable
example: person
ErrorResponse:
type: object
properties:
error:
type: string
description: Error message
example: Model not found
code:
type: integer
example: 404