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Basic AP Is

Basic NLP text processing APIs

const basicAPIsController = new BasicAPIsController(client);

Class Name

BasicAPIsController

Methods

Get Stemmer

Stemmer : Defintion and it's usage

A word takes different inflectional forms. For instance, the word, "Compute" can take the forms, "computing", "computation", and "computerize". The NLP applications such as Search Engines and Information Extraction would want to store the base or stem of the word, i.e "Compute" instead of accomodating all its inflected forms. This will yield in dimensionality reduction and incerases the efficiency of the system. The stemmer cuts the prefix and suffix of a word.

Languages covered:

Our stemmer works for the following 26 languages.

Languages ISO Code
Arabic ar
Catalan ca
Danish da
German de
Greek el
English en
Spanish es
Basque eu
Finnish fi
French fr
Irish ga
Hindi hi
Hungarian hu
Indonesian id
Italian it
Lithuanian lt
Nepali ne
Dutch nl
Norwegian no
Portuguese pt
Romanian ro
Russian ru
Serbian sr
Swedish sv
Tamil ta
Turkish tr 
async getStemmer(
  body: unknown,
  requestOptions?: RequestOptions
): Promise<ApiResponse<Responsestem[]>>

Parameters

Parameter Type Tags Description
body unknown Body, Required Add a JSON Input as per the schema defined below
requestOptions RequestOptions | undefined Optional Pass additional request options.

Response Type

Responsestem[]

Example Usage

const contentType = null;
const body = 'Liquid error: Object of type 'DotLiquid.Hash' cannot be converted to type 'System.String'.';
try {
  const { result, ...httpResponse } = await basicAPIsController.getStemmer(body);
  // Get more response info...
  // const { statusCode, headers } = httpResponse;
} catch(error) {
  if (error instanceof ApiError) {
    const errors = error.result;
    // const { statusCode, headers } = error;
  }
}

Example Response (as JSON)

[
  {
    "orginalText": "அவள்",
    "stem": "அவள்"
  },
  {
    "orginalText": "வேகமாக",
    "stem": "வேகம்"
  },
  {
    "orginalText": "ஓடினாள்",
    "stem": "ஓடி"
  }
]

Errors

HTTP Status Code Error Description Exception Class
400 Error output ErrorsError
426 Please use HTTPS protocol ApiStemmer426Error
429 Too Many Requests ApiError

Get Lemma

Lemmatizer : Defintion and it's usage

Lemmatizer is similar to stemmer that gives the stemmed version of a word but lemmatizer differs from the stemmer in giving a meaningful stem or the lemma. For instance, for the word, "smiling", the stemmer would give, "smil", stemming the suffix, "ing" but the lemmatizer would give the meaningful stem, "smile". lemmatizers can be used in applications such as, Machine Translation, Search Engines, Text Summarization etc.

Languages covered:

Languages ISO Code
Catalan ca
Danish da
Dutch nl
English en
French fr
German de
Greek el
Italian it
Lithuanian lt
Macedonian mk
Norwegian (Bokmål) nb
Polish pl
Portuguese pt
Romanian ro
Russian ru
Spanish es 
async getLemma(
  body: unknown,
  requestOptions?: RequestOptions
): Promise<ApiResponse<Responselemma[]>>

Parameters

Parameter Type Tags Description
body unknown Body, Required Add a JSON Input as per the schema defined below
requestOptions RequestOptions | undefined Optional Pass additional request options.

Response Type

Responselemma[]

Example Usage

const contentType = null;
const body = 'Liquid error: Object of type 'DotLiquid.Hash' cannot be converted to type 'System.String'.';
try {
  const { result, ...httpResponse } = await basicAPIsController.getLemma(body);
  // Get more response info...
  // const { statusCode, headers } = httpResponse;
} catch(error) {
  if (error instanceof ApiError) {
    const errors = error.result;
    // const { statusCode, headers } = error;
  }
}

Example Response (as JSON)

[
  {
    "orginalText": "Smiling",
    "lemmatized": "smile"
  },
  {
    "orginalText": "makes",
    "lemmatized": "make"
  },
  {
    "orginalText": "everyone",
    "lemmatized": "everyone"
  },
  {
    "orginalText": "happy",
    "lemmatized": "happy"
  }
]

Errors

HTTP Status Code Error Description Exception Class
400 Error output ErrorsError
426 Please use HTTPS protocol ApiLemmatize426Error
429 Too Many Requests ApiError

Get Morph

Morphological Analyzer : Defintion and it's usage

Morphological Analyzer analyzes how a word is formed. It breaks a word into smaller units called, "morphemes" and gives a clue on the pattern of words of a particular langauge. It can be used for building applications such as, Machine Translation, Text Summarization, Search systems etc.

Languages covered:

Languages ISO Code
Catalan ca
Danish da
Dutch nl
English en
French fr
German de
Greek el
Italian it
Japanese ja
Lithuanian lt
Macedonian mk
Norwegian (Bokmål) nb
Polish pl
Portuguese pt
Russian ru
Spanish es 
async getMorph(
  body: unknown,
  requestOptions?: RequestOptions
): Promise<ApiResponse<Responsemorph>>

Parameters

Parameter Type Tags Description
body unknown Body, Required Add a JSON Input as per the schema defined below
requestOptions RequestOptions | undefined Optional Pass additional request options.

Response Type

Responsemorph

Example Usage

const contentType = null;
const body = 'Liquid error: Object of type 'DotLiquid.Hash' cannot be converted to type 'System.String'.';
try {
  const { result, ...httpResponse } = await basicAPIsController.getMorph(body);
  // Get more response info...
  // const { statusCode, headers } = httpResponse;
} catch(error) {
  if (error instanceof ApiError) {
    const errors = error.result;
    // const { statusCode, headers } = error;
  }
}

Example Response (as JSON)

{
  "Let": {
    "VerbForm": [
      "Inf"
    ],
    "Case": [
      "Acc"
    ],
    "Number": [
      "Sing"
    ],
    "Person": [
      "1"
    ],
    "PronType": [
      "Art"
    ],
    "Definite": [
      "Def"
    ],
    "NounType": [
      "Prop"
    ]
  },
  "us": {
    "VerbForm": [
      "Inf"
    ],
    "Case": [
      "Acc"
    ],
    "Number": [
      "Sing"
    ],
    "Person": [
      "1"
    ],
    "PronType": [
      "Art"
    ],
    "Definite": [
      "Def"
    ],
    "NounType": [
      "Prop"
    ]
  },
  "begin": {
    "VerbForm": [
      "Inf"
    ],
    "Case": [
      "Acc"
    ],
    "Number": [
      "Sing"
    ],
    "Person": [
      "1"
    ],
    "PronType": [
      "Art"
    ],
    "Definite": [
      "Def"
    ],
    "NounType": [
      "Prop"
    ]
  },
  "the": {
    "VerbForm": [
      "Inf"
    ],
    "Case": [
      "Acc"
    ],
    "Number": [
      "Sing"
    ],
    "Person": [
      "1"
    ],
    "PronType": [
      "Art"
    ],
    "Definite": [
      "Def"
    ],
    "NounType": [
      "Prop"
    ]
  },
  "API": {
    "VerbForm": [
      "Inf"
    ],
    "Case": [
      "Acc"
    ],
    "Number": [
      "Sing"
    ],
    "Person": [
      "1"
    ],
    "PronType": [
      "Art"
    ],
    "Definite": [
      "Def"
    ],
    "NounType": [
      "Prop"
    ]
  },
  "development": {
    "VerbForm": [
      "Inf"
    ],
    "Case": [
      "Acc"
    ],
    "Number": [
      "Sing"
    ],
    "Person": [
      "1"
    ],
    "PronType": [
      "Art"
    ],
    "Definite": [
      "Def"
    ],
    "NounType": [
      "Prop"
    ]
  },
  ".": {
    "VerbForm": [
      "Inf"
    ],
    "Case": [
      "Acc"
    ],
    "Number": [
      "Sing"
    ],
    "Person": [
      "1"
    ],
    "PronType": [
      "Art"
    ],
    "Definite": [
      "Def"
    ],
    "NounType": [
      "Prop"
    ]
  }
}

Errors

HTTP Status Code Error Description Exception Class
400 Error output ErrorsError
426 Please use HTTPS protocol ApiMorph426Error
429 Too Many Requests ApiError

Get Postag

Parts of Speech Tagger : Defintion and it's usage

Parts of Speech Tagger, which is shortly known as POS Tagger is a software that automatically finds the word classes, when a text input is given. The text input can be a word, a sentence or a set of sentences. The word classes are the grammatical categories such as, Noun, Verb, Adverb etc. The category assigned to each word is called as a tag. A set of tags, each indicating a grammatical category is called, "tagsets". POS tagging is a mandatory pre-processing for most of the Natural Language Processing Applications such as, Information Extraction, Information Retreival systems and Summary generation systems. A POS Tagger is a language-dependent software as the grammar rules will differ for every language. For instance, a word ending with "ing" might indicate a "Verb" in English but this will not be applicable for other languages.

Languages covered:

Languages ISO Code
Chinese zh
Dutch nl
English en
German de
Italian it
Lithuanian lt
Polish pl
Romanian ro
Tamil ta 
async getPostag(
  body: unknown,
  requestOptions?: RequestOptions
): Promise<ApiResponse<Responsepo[]>>

Parameters

Parameter Type Tags Description
body unknown Body, Required Add a JSON Input as per the schema defined below
requestOptions RequestOptions | undefined Optional Pass additional request options.

Response Type

Responsepo[]

Example Usage

const contentType = null;
const body = 'Liquid error: Object of type 'DotLiquid.Hash' cannot be converted to type 'System.String'.';
try {
  const { result, ...httpResponse } = await basicAPIsController.getPostag(body);
  // Get more response info...
  // const { statusCode, headers } = httpResponse;
} catch(error) {
  if (error instanceof ApiError) {
    const errors = error.result;
    // const { statusCode, headers } = error;
  }
}

Example Response (as JSON)

[
  {
    "orginalText": "Let",
    "postag": "VERB"
  },
  {
    "orginalText": "us",
    "postag": "PRON"
  },
  {
    "orginalText": "begin",
    "postag": "VERB"
  },
  {
    "orginalText": "the",
    "postag": "DET"
  },
  {
    "orginalText": "API",
    "postag": "PROPN"
  },
  {
    "orginalText": "development",
    "postag": "NOUN"
  },
  {
    "orginalText": ".",
    "postag": "PUNCT"
  }
]

Errors

HTTP Status Code Error Description Exception Class
400 Error output ErrorsError
426 Please use HTTPS protocol ApiPostag426Error
429 Too Many Requests ApiError