Natural Language Processing APIv2 API Reference

The powerful Natural Language Processing APIs let you perform part of speech tagging, entity identification, sentence parsing, and much more to help you understand the meaning of unstructured text.

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API Endpoint

https://api.cloudmersive.com

Schemes: https

Version: v1

Authentication

Apikey

API Key Authentication

type

apiKey

name

Apikey

header

Analytics

Perform Sentiment Analysis and Classification on Text

POST /nlp-v2/analytics/sentiment

Analyze input text using advanced Sentiment Analysis to determine if the input is positive, negative, or neutral. Supports English language input. Consumes 1-2 API calls per sentence.

SentimentAnalysisRequest

Input sentiment analysis request

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "TextToAnalyze": "string"
}

200 OK

SentimentAnalysisResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "SentimentClassificationResult": "string",
  "SentimentScoreResult": "number (double)",
  "SentenceCount": "integer (int32)"
}


Apikey

Analytics

Perform Profanity and Obscene Language Analysis and Detection on Text

POST /nlp-v2/analytics/profanity

Analyze input text using advanced Profanity and Obscene Language Analysis to determine if the input contains profane language. Supports English language input. Consumes 1-2 API calls per sentence.

ProfanityAnalysisRequest

Input profanity analysis request

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "TextToAnalyze": "string"
}

200 OK

ProfanityAnalysisResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "ProfanityScoreResult": "number (double)",
  "SentenceCount": "integer (int32)"
}


Apikey

Analytics

Perform Hate Speech Analysis and Detection on Text

POST /nlp-v2/analytics/hate-speech

Analyze input text using advanced Hate Speech Analysis to determine if the input contains hate speech language. Supports English language input. Consumes 1-2 API calls per sentence.

HateSpeechAnalysisRequest

Input hate speech analysis request

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "TextToAnalyze": "string"
}

200 OK

HateSpeechAnalysisResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "HateSpeechScoreResult": "number (double)",
  "SentenceCount": "integer (int32)"
}


Apikey

Analytics

Perform Subjectivity and Objectivity Analysis on Text

POST /nlp-v2/analytics/subjectivity

Analyze input text using advanced Subjectivity and Objectivity Language Analysis to determine if the input text is objective or subjective, and how much. Supports English language input. Consumes 1-2 API calls per sentence.

SubjectivityAnalysisRequest

Input subjectivity analysis request

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "TextToAnalyze": "string"
}

200 OK

SubjectivityAnalysisResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "SubjectivityScoreResult": "number (double)",
  "SentenceCount": "integer (int32)"
}


Apikey

Analytics

Perform Semantic Similarity Comparison of Two Strings

POST /nlp-v2/analytics/similarity

Analyze two input text strings, typically sentences, and determine the semantic similarity of each. Semantic similarity refers to the degree to which two sentences mean the same thing semantically. Uses advanced Deep Learning to perform the semantic similarity comparison. Consumes 1-2 API calls per sentence.

SimilarityAnalysisRequest

Input similarity analysis request

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "TextToAnalyze1": "string",
  "TextToAnalyze2": "string"
}

200 OK

SimilarityAnalysisResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "SimilarityScoreResult": "number (double)",
  "SentenceCount": "integer (int32)"
}


Apikey

ExtractEntities

Extract entities from string

POST /nlp-v2/extract-entities

Extract the named entitites from an input string.

ExtractEntitiesRequest

Input string

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "InputString": "string"
}

200 OK

ExtractEntitiesResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "Entities": [
    {
      "EntityType": "string",
      "EntityText": "string"
    }
  ]
}


Apikey

LanguageDetection

Detect language of text

POST /nlp-v2/language/detect

Automatically determine which language a text string is written in. Supports Danish (DAN), German (DEU), English (ENG), French (FRA), Italian (ITA), Japanese (JPN), Korean (KOR), Dutch (NLD), Norwegian (NOR), Portuguese (POR), Russian (RUS), Spanish (SPA), Swedish (SWE), Chinese (ZHO).

LanguageDetectionRequest

undefined

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "textToDetect": "string"
}

200 OK

LanguageDetectionResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "DetectedLanguage_ThreeLetterCode": "string",
  "DetectedLanguage_FullName": "string"
}


Apikey

LanguageTranslation

Translate German to English text with Deep Learning AI

POST /nlp-v2/translate/language/deu/to/eng

Automatically translates input text in German to output text in English using advanced Deep Learning and Neural NLP. Consumes 1-2 API calls per input sentence.

LanguageTranslationRequest

Input translation request

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "TextToTranslate": "string"
}

200 OK

LanguageTranslationResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "TranslatedTextResult": "string",
  "SentenceCount": "integer (int32)"
}


Apikey

LanguageTranslation

Translate English to German text with Deep Learning AI

POST /nlp-v2/translate/language/eng/to/deu

Automatically translates input text in English to output text in German using advanced Deep Learning and Neural NLP. Consumes 1-2 API calls per input sentence.

LanguageTranslationRequest

Input translation request

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "TextToTranslate": "string"
}

200 OK

LanguageTranslationResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "TranslatedTextResult": "string",
  "SentenceCount": "integer (int32)"
}


Apikey

LanguageTranslation

Translate French to English text with Deep Learning AI

POST /nlp-v2/translate/language/fra/to/eng

Automatically translates input text in French to output text in English using advanced Deep Learning and Neural NLP. Consumes 1-2 API calls per input sentence.

LanguageTranslationRequest

Input translation request

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "TextToTranslate": "string"
}

200 OK

LanguageTranslationResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "TranslatedTextResult": "string",
  "SentenceCount": "integer (int32)"
}


Apikey

LanguageTranslation

Translate English to French text with Deep Learning AI

POST /nlp-v2/translate/language/eng/to/fra

Automatically translates input text in English to output text in French using advanced Deep Learning and Neural NLP. Consumes 1-2 API calls per input sentence.

LanguageTranslationRequest

Input translation request

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "TextToTranslate": "string"
}

200 OK

LanguageTranslationResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "TranslatedTextResult": "string",
  "SentenceCount": "integer (int32)"
}


Apikey

LanguageTranslation

Translate Russian to English text with Deep Learning AI

POST /nlp-v2/translate/language/rus/to/eng

Automatically translates input text in Russian to output text in English using advanced Deep Learning and Neural NLP. Consumes 1-2 API calls per input sentence.

LanguageTranslationRequest

Input translation request

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "TextToTranslate": "string"
}

200 OK

LanguageTranslationResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "TranslatedTextResult": "string",
  "SentenceCount": "integer (int32)"
}


Apikey

LanguageTranslation

Translate English to Russian text with Deep Learning AI

POST /nlp-v2/translate/language/eng/to/rus

Automatically translates input text in English to output text in Russian using advanced Deep Learning and Neural NLP. Consumes 1-2 API calls per input sentence.

LanguageTranslationRequest

Input translation request

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "TextToTranslate": "string"
}

200 OK

LanguageTranslationResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "TranslatedTextResult": "string",
  "SentenceCount": "integer (int32)"
}


Apikey

Parse

Parse string to syntax tree

POST /nlp-v2/parse/tree

Parses the input string into a Penn Treebank syntax tree

ParseRequest

Input string

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "InputString": "string"
}

200 OK

ParseResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "ParseTree": "string"
}


Apikey

PosTagger

Part-of-speech tag a string

POST /nlp-v2/pos/tag/sentence

Part-of-speech (POS) tag a string and return result as JSON

PosRequest

Input string

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "InputText": "string"
}

200 OK

PosResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "TaggedSentences": [
    {
      "Words": [
        {
          "Word": "object",
          "Tag": "object"
        }
      ]
    }
  ]
}


Apikey

PosTagger

Part-of-speech tag a string, filter to verbs

POST /nlp-v2/pos/tag/verbs

Part-of-speech (POS) tag a string, find the verbs, and return result as JSON

PosRequest

Input string

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "InputText": "string"
}

200 OK

PosResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "TaggedSentences": [
    {
      "Words": [
        {
          "Word": "object",
          "Tag": "object"
        }
      ]
    }
  ]
}


Apikey

PosTagger

Part-of-speech tag a string, filter to nouns

POST /nlp-v2/pos/tag/nouns

Part-of-speech (POS) tag a string, find the nouns, and return result as JSON

PosRequest

Input string

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "InputText": "string"
}

200 OK

PosResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "TaggedSentences": [
    {
      "Words": [
        {
          "Word": "object",
          "Tag": "object"
        }
      ]
    }
  ]
}


Apikey

PosTagger

Part-of-speech tag a string, filter to adjectives

POST /nlp-v2/pos/tag/adjectives

Part-of-speech (POS) tag a string, find the adjectives, and return result as JSON

PosRequest

Input string

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "InputText": "string"
}

200 OK

PosResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "TaggedSentences": [
    {
      "Words": [
        {
          "Word": "object",
          "Tag": "object"
        }
      ]
    }
  ]
}


Apikey

PosTagger

Part-of-speech tag a string, filter to adverbs

POST /nlp-v2/pos/tag/adverbs

Part-of-speech (POS) tag a string, find the adverbs, and return result as JSON

PosRequest

Input string

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "InputText": "string"
}

200 OK

PosResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "TaggedSentences": [
    {
      "Words": [
        {
          "Word": "object",
          "Tag": "object"
        }
      ]
    }
  ]
}


Apikey

PosTagger

Part-of-speech tag a string, filter to pronouns

POST /nlp-v2/pos/tag/pronouns

Part-of-speech (POS) tag a string, find the pronouns, and return result as JSON

PosRequest

Input string

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "InputText": "string"
}

200 OK

PosResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "TaggedSentences": [
    {
      "Words": [
        {
          "Word": "object",
          "Tag": "object"
        }
      ]
    }
  ]
}


Apikey

Rephrase

Rephrase, paraphrase English text sentence-by-sentence using Deep Learning AI

POST /nlp-v2/rephrase/rephrase/eng/by-sentence

Automatically rephrases or paraphrases input text in English sentence by sentence using advanced Deep Learning and Neural NLP. Creates multiple reprhasing candidates per input sentence, from 1 to 10 possible rephrasings of the original sentence. Seeks to preserve original semantic meaning in rephrased output candidates. Consumes 1-2 API calls per output rephrasing option generated, per sentence.

RephraseRequest

Input rephrase request

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "TextToTranslate": "string",
  "TargetRephrasingCount": "integer (int32)"
}

200 OK

RephraseResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "RephrasedResults": [
    {
      "SentenceIndex": "integer (int32)",
      "OriginalSentenceText": "string",
      "Rephrasings": [
        {
          "RephrasedOptionIndex": "integer (int32)",
          "RephrasedSentenceText": "string"
        }
      ]
    }
  ],
  "SentenceCount": "integer (int32)"
}


Apikey

Segmentation

Extract sentences from string

POST /nlp-v2/segmentation/sentences

Segment an input string into separate sentences, output result as a string.

SentenceSegmentationRequest

Input string

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "InputString": "string"
}

200 OK

SentenceSegmentationResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Successful": "boolean",
  "Sentences": [
    "string"
  ],
  "SentenceCount": "integer (int32)"
}


Apikey

Segmentation

Get words in input string

POST /nlp-v2/segmentation/words

Get the component words in an input string

GetWordsRequest

String to process

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "InputText": "string"
}

200 OK

GetWordsResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Words": [
    {
      "Word": "string",
      "WordIndex": "integer (int32)",
      "StartPosition": "integer (int32)",
      "EndPosition": "integer (int32)"
    }
  ]
}


Apikey

Spellcheck

Find spelling corrections

POST /nlp-v2/spellcheck/check/word

Find spelling correction suggestions and return result as JSON

CheckWordRequest

Input string

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "Word": "string"
}

200 OK

CheckWordResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "Correct": "boolean",
  "Suggestions": [
    "string"
  ]
}


Apikey

Spellcheck

Check if sentence is spelled correctly

POST /nlp-v2/spellcheck/check/sentence

Checks whether the sentence is spelled correctly and returns the result as JSON

CheckSentenceRequest

Input sentence

Code Example:

Request Content-Types: application/json, text/json, application/xml, text/xml, application/x-www-form-urlencoded

Request Example

{
  "Sentence": "string"
}

200 OK

CheckSentenceResponse

Response Content-Types: application/json

Response Example (200 OK)

{
  "IncorrectCount": "integer (int32)",
  "Words": [
    {
      "Word": {
        "Word": "string",
        "WordIndex": "integer (int32)",
        "StartPosition": "integer (int32)",
        "EndPosition": "integer (int32)"
      },
      "Correct": "boolean",
      "Suggestions": [
        "string"
      ]
    }
  ]
}


Apikey

Schema Definitions

SentimentAnalysisRequest: object

Input to a sentiment analysis operation

TextToAnalyze: string: Text to analyze

Example

{
  "TextToAnalyze": "string"
}

SentimentAnalysisResponse: object

Output of a sentiment analysis operation

Successful: boolean: True if the sentiment analysis operation was successful, false otherwise
SentimentClassificationResult: string: Classification of input text into a sentiment classification; possible values are "Positive", "Negative" or "Neutral"
SentimentScoreResult: number (double): Sentiment classification score between -1.0 and +1.0 where scores less than 0 are negative sentiment, scores greater than 0 are positive sentiment and scores close to 0 are neutral. The greater the value deviates from 0.0 the stronger the sentiment, with +1.0 and -1.0 being maximum positive and negative sentiment, respectively.
SentenceCount: integer (int32): Number of sentences in input text

Example

{
  "Successful": "boolean",
  "SentimentClassificationResult": "string",
  "SentimentScoreResult": "number (double)",
  "SentenceCount": "integer (int32)"
}

ProfanityAnalysisRequest: object

Input to a profanity analysis operation

TextToAnalyze: string: Text to analyze

Example

{
  "TextToAnalyze": "string"
}

ProfanityAnalysisResponse: object

Output of a profanity analysis operation

Successful: boolean: True if the profanity detection operation was successful, false otherwise
ProfanityScoreResult: number (double): Profanity classification score between 0.0 and 1.0 where scores closer to zero have a low probability of being profane or contain obscene language, while scores close to 1.0 have a high probability of being profane or containing obscene language. Values above 0.8 have a very high probability of being profane.
SentenceCount: integer (int32): Number of sentences in input text

Example

{
  "Successful": "boolean",
  "ProfanityScoreResult": "number (double)",
  "SentenceCount": "integer (int32)"
}

HateSpeechAnalysisRequest: object

Input to a hate speech analysis operation

TextToAnalyze: string: Text to analyze

Example

{
  "TextToAnalyze": "string"
}

HateSpeechAnalysisResponse: object

Output of a hate speech analysis operation

Successful: boolean: True if the profanity detection operation was successful, false otherwise
HateSpeechScoreResult: number (double): Hate speech classification score between 0.0 and 1.0 where scores closer to zero have a low probability of being hate speech language, while scores close to 1.0 have a high probability of being hate speech language. Values above 0.8 have a very high probability of being hate speech.
SentenceCount: integer (int32): Number of sentences in input text

Example

{
  "Successful": "boolean",
  "HateSpeechScoreResult": "number (double)",
  "SentenceCount": "integer (int32)"
}

SubjectivityAnalysisRequest: object

Input to a subjectivity analysis operation

TextToAnalyze: string: Text to analyze

Example

{
  "TextToAnalyze": "string"
}

SubjectivityAnalysisResponse: object

Output of a subjectivity analysis operation

Successful: boolean: True if the subjectivity analysis operation was successful, false otherwise
SubjectivityScoreResult: number (double): Subjectivity vs. objectivity classification score between 0.0 and 1.0 where scores closer to zero have a high probability of objectivity, while scores close to 1.0 have a high probability of subjectivity.
SentenceCount: integer (int32): Number of sentences in input text

Example

{
  "Successful": "boolean",
  "SubjectivityScoreResult": "number (double)",
  "SentenceCount": "integer (int32)"
}

SimilarityAnalysisRequest: object

Input to a similarity analysis operation

TextToAnalyze1: string: First text to analyze
TextToAnalyze2: string: Second text to analyze

Example

{
  "TextToAnalyze1": "string",
  "TextToAnalyze2": "string"
}

SimilarityAnalysisResponse: object

Output of a similarity analysis operation

Successful: boolean: True if the similarity analysis operation was successful, false otherwise
SimilarityScoreResult: number (double): Similarity score between 0.0 and 1.0 where scores closer to zero have a low probability of semantic similarity, while scores close to 1.0 have a high probability of semantic similarity.
SentenceCount: integer (int32): Number of sentences in input text

Example

{
  "Successful": "boolean",
  "SimilarityScoreResult": "number (double)",
  "SentenceCount": "integer (int32)"
}

ExtractEntitiesRequest: object

Request to extract named entities

InputString: string: Input string to extract entities from

Example

{
  "InputString": "string"
}

ExtractEntitiesResponse: object

Result of performing an extract entities operation

Successful: boolean: True if the operation was successful, false otherwise
Entities: Entity
Entity

Example

{
  "Successful": "boolean",
  "Entities": [
    {
      "EntityType": "string",
      "EntityText": "string"
    }
  ]
}

Entity: object

EntityType: string
EntityText: string

Example

{
  "EntityType": "string",
  "EntityText": "string"
}

LanguageDetectionRequest: object

Input to a language detection operation

textToDetect: string: Text to detect the language of

Example

{
  "textToDetect": "string"
}

LanguageDetectionResponse: object

Output of a language detection operation

Successful: boolean: True if the language detection operation was successful, false otherwise
DetectedLanguage_ThreeLetterCode: string: ISO 639 three letter language code
DetectedLanguage_FullName: string: The full name (in English) of the detected language

Example

{
  "Successful": "boolean",
  "DetectedLanguage_ThreeLetterCode": "string",
  "DetectedLanguage_FullName": "string"
}

LanguageTranslationRequest: object

Input to a language translation operation

TextToTranslate: string: Text to translate

Example

{
  "TextToTranslate": "string"
}

LanguageTranslationResponse: object

Output of a language translation operation

Successful: boolean: True if the language detection operation was successful, false otherwise
TranslatedTextResult: string: Translated text in target language
SentenceCount: integer (int32): Number of sentences in input text

Example

{
  "Successful": "boolean",
  "TranslatedTextResult": "string",
  "SentenceCount": "integer (int32)"
}

ParseRequest: object

Linguistic parse request

InputString: string: Input string to linguistically parse

Example

{
  "InputString": "string"
}

ParseResponse: object

Result of linguistic parse operation

ParseTree: string: Parse tree in Penn Treebank syntax tree format

Example

{
  "ParseTree": "string"
}

PosRequest: object

Part of speech tagging request

InputText: string: Input text string

Example

{
  "InputText": "string"
}

PosResponse: object

Part of speech tag result

TaggedSentences: PosSentence: Sentences in the string
PosSentence

Example

{
  "TaggedSentences": [
    {
      "Words": [
        {
          "Word": "object",
          "Tag": "object"
        }
      ]
    }
  ]
}

PosSentence: object

Sentence in a POS tag result

Words: PosTaggedWord: Words in the sentence
PosTaggedWord

Example

{
  "Words": [
    {
      "Word": "object",
      "Tag": "object"
    }
  ]
}

PosTaggedWord: object

Word tagged in a POS tag

Word: object: Word that was tagged
Tag: object: Penn Treebank tag applied to the word

Example

{
  "Word": "object",
  "Tag": "object"
}

RephraseRequest: object

Input to a text rephrasing operation

TextToTranslate: string: Text to rephrase
TargetRephrasingCount: integer (int32): The number of rephrasing output options you would like per sentence; possible values are 1 to 10. Default is 2.

Example

{
  "TextToTranslate": "string",
  "TargetRephrasingCount": "integer (int32)"
}

RephraseResponse: object

Output of a text rephrasing operation

Successful: boolean: True if the language detection operation was successful, false otherwise
RephrasedResults: RephrasedSentence: Results of the rephrasing, paraphrasing operation, in the order of the input sentences
RephrasedSentence
SentenceCount: integer (int32): Number of sentences in input text

Example

{
  "Successful": "boolean",
  "RephrasedResults": [
    {
      "SentenceIndex": "integer (int32)",
      "OriginalSentenceText": "string",
      "Rephrasings": [
        {
          "RephrasedOptionIndex": "integer (int32)",
          "RephrasedSentenceText": "string"
        }
      ]
    }
  ],
  "SentenceCount": "integer (int32)"
}

RephrasedSentence: object

One input sentence and associated rephrasing results

SentenceIndex: integer (int32): Index of the sentence, 1-based, ordered
OriginalSentenceText: string: Original input sentence text
Rephrasings: RephrasedSentenceOption: Rephrasing text options, candidates of the original input sentence, in order - with best candidate first
RephrasedSentenceOption

Example

{
  "SentenceIndex": "integer (int32)",
  "OriginalSentenceText": "string",
  "Rephrasings": [
    {
      "RephrasedOptionIndex": "integer (int32)",
      "RephrasedSentenceText": "string"
    }
  ]
}

RephrasedSentenceOption: object

One rephrasing of an original input sentence

RephrasedOptionIndex: integer (int32): Ordered index of the rephrasing option, 1-based, with 1 being the best option
RephrasedSentenceText: string: One sentence of output rephrased text of original input sentence

Example

{
  "RephrasedOptionIndex": "integer (int32)",
  "RephrasedSentenceText": "string"
}

SentenceSegmentationRequest: object

InputString: string

Example

{
  "InputString": "string"
}

SentenceSegmentationResponse: object

Successful: boolean
Sentences: string[]
string
SentenceCount: integer (int32)

Example

{
  "Successful": "boolean",
  "Sentences": [
    "string"
  ],
  "SentenceCount": "integer (int32)"
}

GetWordsRequest: object

InputText: string

Example

{
  "InputText": "string"
}

GetWordsResponse: object

Words in input string

Words: WordPosition: Array of words
WordPosition

Example

{
  "Words": [
    {
      "Word": "string",
      "WordIndex": "integer (int32)",
      "StartPosition": "integer (int32)",
      "EndPosition": "integer (int32)"
    }
  ]
}

WordPosition: object

Word: string: Word as a string
WordIndex: integer (int32): Zero-based index of the word; first word has index 0, second word has index 1 and so on
StartPosition: integer (int32): Zero-based character offset at which the word begins in the input string
EndPosition: integer (int32): Zero-based character offset at which the word ends in the input string

Example

{
  "Word": "string",
  "WordIndex": "integer (int32)",
  "StartPosition": "integer (int32)",
  "EndPosition": "integer (int32)"
}

CheckWordRequest: object

Word: string

Example

{
  "Word": "string"
}

CheckWordResponse: object

Spelling correction check result

Correct: boolean: True if the word is spelled correctly, false otherwise
Suggestions: string[]: Suggested spelling corrections
string

Example

{
  "Correct": "boolean",
  "Suggestions": [
    "string"
  ]
}

CheckSentenceRequest: object

Input object for spell checking

Sentence: string: Input sentence for spell check

Example

{
  "Sentence": "string"
}

CheckSentenceResponse: object

Result of spell checking a sentence

IncorrectCount: integer (int32): Number of incorrect words
Words: CorrectWordInSentence: Words in the sentence, both correct and incorrect
CorrectWordInSentence

Example

{
  "IncorrectCount": "integer (int32)",
  "Words": [
    {
      "Word": {
        "Word": "string",
        "WordIndex": "integer (int32)",
        "StartPosition": "integer (int32)",
        "EndPosition": "integer (int32)"
      },
      "Correct": "boolean",
      "Suggestions": [
        "string"
      ]
    }
  ]
}

CorrectWordInSentence: object

A word in a sentence

Word: WordPosition: Position of the word
Correct: boolean: True if the word is spelled correctly, false otherwise
Suggestions: string[]: Suggested spelling improvements
string

Example

{
  "Word": {
    "Word": "string",
    "WordIndex": "integer (int32)",
    "StartPosition": "integer (int32)",
    "EndPosition": "integer (int32)"
  },
  "Correct": "boolean",
  "Suggestions": [
    "string"
  ]
}