Types overview

AnalyzeEntitiesRequest

The entity analysis request message.

Fields
`document`	`object (Document)` Required. Input document.
`encodingType`	`enum` The encoding type used by the API to calculate offsets.
Enum type. Can be one of the following:
`NONE`	If `EncodingType` is not specified, encoding-dependent information (such as `begin_offset`) will be set at `-1`.
`UTF8`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-8 encoding of the input. C++ and Go are examples of languages that use this encoding natively.
`UTF16`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-16 encoding of the input. Java and JavaScript are examples of languages that use this encoding natively.
`UTF32`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-32 encoding of the input. Python is an example of a language that uses this encoding natively.

AnalyzeEntitiesResponse

The entity analysis response message.

Fields

Fields
`entities[]`	`object (Entity)` The recognized entities in the input document.
`language`	`string` The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.

entities[]

object (Entity)

The recognized entities in the input document.

language

string

The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.

AnalyzeEntitySentimentRequest

The entity-level sentiment analysis request message.

Fields
`document`	`object (Document)` Required. Input document.
`encodingType`	`enum` The encoding type used by the API to calculate offsets.
Enum type. Can be one of the following:
`NONE`	If `EncodingType` is not specified, encoding-dependent information (such as `begin_offset`) will be set at `-1`.
`UTF8`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-8 encoding of the input. C++ and Go are examples of languages that use this encoding natively.
`UTF16`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-16 encoding of the input. Java and JavaScript are examples of languages that use this encoding natively.
`UTF32`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-32 encoding of the input. Python is an example of a language that uses this encoding natively.

AnalyzeEntitySentimentResponse

The entity-level sentiment analysis response message.

Fields

Fields
`entities[]`	`object (Entity)` The recognized entities in the input document with associated sentiments.
`language`	`string` The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.

entities[]

object (Entity)

The recognized entities in the input document with associated sentiments.

language

string

The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.

AnalyzeSentimentRequest

The sentiment analysis request message.

Fields
`document`	`object (Document)` Required. Input document.
`encodingType`	`enum` The encoding type used by the API to calculate sentence offsets.
Enum type. Can be one of the following:
`NONE`	If `EncodingType` is not specified, encoding-dependent information (such as `begin_offset`) will be set at `-1`.
`UTF8`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-8 encoding of the input. C++ and Go are examples of languages that use this encoding natively.
`UTF16`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-16 encoding of the input. Java and JavaScript are examples of languages that use this encoding natively.
`UTF32`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-32 encoding of the input. Python is an example of a language that uses this encoding natively.

AnalyzeSentimentResponse

The sentiment analysis response message.

Fields

Fields
`documentSentiment`	`object (Sentiment)` The overall sentiment of the input document.
`language`	`string` The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.
`sentences[]`	`object (Sentence)` The sentiment for all the sentences in the document.

documentSentiment

object (Sentiment)

The overall sentiment of the input document.

language

string

The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.

sentences[]

object (Sentence)

The sentiment for all the sentences in the document.

AnalyzeSyntaxRequest

The syntax analysis request message.

Fields
`document`	`object (Document)` Required. Input document.
`encodingType`	`enum` The encoding type used by the API to calculate offsets.
Enum type. Can be one of the following:
`NONE`	If `EncodingType` is not specified, encoding-dependent information (such as `begin_offset`) will be set at `-1`.
`UTF8`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-8 encoding of the input. C++ and Go are examples of languages that use this encoding natively.
`UTF16`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-16 encoding of the input. Java and JavaScript are examples of languages that use this encoding natively.
`UTF32`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-32 encoding of the input. Python is an example of a language that uses this encoding natively.

AnalyzeSyntaxResponse

The syntax analysis response message.

Fields

Fields
`language`	`string` The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.
`sentences[]`	`object (Sentence)` Sentences in the input document.
`tokens[]`	`object (Token)` Tokens, along with their syntactic information, in the input document.

language

string

The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.

sentences[]

object (Sentence)

Sentences in the input document.

tokens[]

object (Token)

Tokens, along with their syntactic information, in the input document.

AnnotateTextRequest

The request message for the text annotation API, which can perform multiple analysis types (sentiment, entities, and syntax) in one call.

Fields
`document`	`object (Document)` Required. Input document.
`encodingType`	`enum` The encoding type used by the API to calculate offsets.
Enum type. Can be one of the following:
`NONE`	If `EncodingType` is not specified, encoding-dependent information (such as `begin_offset`) will be set at `-1`.
`UTF8`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-8 encoding of the input. C++ and Go are examples of languages that use this encoding natively.
`UTF16`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-16 encoding of the input. Java and JavaScript are examples of languages that use this encoding natively.
`UTF32`	Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-32 encoding of the input. Python is an example of a language that uses this encoding natively.

`features`	`object (Features)` Required. The enabled features.

AnnotateTextResponse

The text annotations response message.

Fields
`categories[]`	`object (ClassificationCategory)` Categories identified in the input document.
`documentSentiment`	`object (Sentiment)` The overall sentiment for the document. Populated if the user enables AnnotateTextRequest.Features.extract_document_sentiment.
`entities[]`	`object (Entity)` Entities, along with their semantic information, in the input document. Populated if the user enables AnnotateTextRequest.Features.extract_entities.
`language`	`string` The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.
`sentences[]`	`object (Sentence)` Sentences in the input document. Populated if the user enables AnnotateTextRequest.Features.extract_syntax.
`tokens[]`	`object (Token)` Tokens, along with their syntactic information, in the input document. Populated if the user enables AnnotateTextRequest.Features.extract_syntax.

ClassificationCategory

Represents a category returned from the text classifier.

Fields

Fields
`confidence`	`number (float format)` The classifier's confidence of the category. Number represents how certain the classifier is that this category represents the given text.
`name`	`string` The name of the category representing the document, from the predefined taxonomy.

confidence

number (float format)

The classifier's confidence of the category. Number represents how certain the classifier is that this category represents the given text.

name

string

The name of the category representing the document, from the predefined taxonomy.

ClassifyTextRequest

The document classification request message.

Fields

document

object (Document)

Required. Input document.

ClassifyTextResponse

The document classification response message.

Fields

Fields
`categories[]`	`object (ClassificationCategory)` Categories representing the input document.

categories[]

object (ClassificationCategory)

Categories representing the input document.

DependencyEdge

Represents dependency parse tree information for a token. (For more information on dependency labels, see http://www.aclweb.org/anthology/P13-2017

Fields
`headTokenIndex`	`integer (int32 format)` Represents the head of this token in the dependency tree. This is the index of the token which has an arc going to this token. The index is the position of the token in the array of tokens returned by the API method. If this token is a root token, then the `head_token_index` is its own index.
`label`	`enum` The parse label for the token.
Enum type. Can be one of the following:
`UNKNOWN`	Unknown
`ABBREV`	Abbreviation modifier
`ACOMP`	Adjectival complement
`ADVCL`	Adverbial clause modifier
`ADVMOD`	Adverbial modifier
`AMOD`	Adjectival modifier of an NP
`APPOS`	Appositional modifier of an NP
`ATTR`	Attribute dependent of a copular verb
`AUX`	Auxiliary (non-main) verb
`AUXPASS`	Passive auxiliary
`CC`	Coordinating conjunction
`CCOMP`	Clausal complement of a verb or adjective
`CONJ`	Conjunct
`CSUBJ`	Clausal subject
`CSUBJPASS`	Clausal passive subject
`DEP`	Dependency (unable to determine)
`DET`	Determiner
`DISCOURSE`	Discourse
`DOBJ`	Direct object
`EXPL`	Expletive
`GOESWITH`	Goes with (part of a word in a text not well edited)
`IOBJ`	Indirect object
`MARK`	Marker (word introducing a subordinate clause)
`MWE`	Multi-word expression
`MWV`	Multi-word verbal expression
`NEG`	Negation modifier
`NN`	Noun compound modifier
`NPADVMOD`	Noun phrase used as an adverbial modifier
`NSUBJ`	Nominal subject
`NSUBJPASS`	Passive nominal subject
`NUM`	Numeric modifier of a noun
`NUMBER`	Element of compound number
`P`	Punctuation mark
`PARATAXIS`	Parataxis relation
`PARTMOD`	Participial modifier
`PCOMP`	The complement of a preposition is a clause
`POBJ`	Object of a preposition
`POSS`	Possession modifier
`POSTNEG`	Postverbal negative particle
`PRECOMP`	Predicate complement
`PRECONJ`	Preconjunt
`PREDET`	Predeterminer
`PREF`	Prefix
`PREP`	Prepositional modifier
`PRONL`	The relationship between a verb and verbal morpheme
`PRT`	Particle
`PS`	Associative or possessive marker
`QUANTMOD`	Quantifier phrase modifier
`RCMOD`	Relative clause modifier
`RCMODREL`	Complementizer in relative clause
`RDROP`	Ellipsis without a preceding predicate
`REF`	Referent
`REMNANT`	Remnant
`REPARANDUM`	Reparandum
`ROOT`	Root
`SNUM`	Suffix specifying a unit of number
`SUFF`	Suffix
`TMOD`	Temporal modifier
`TOPIC`	Topic marker
`VMOD`	Clause headed by an infinite form of the verb that modifies a noun
`VOCATIVE`	Vocative
`XCOMP`	Open clausal complement
`SUFFIX`	Name suffix
`TITLE`	Name title
`ADVPHMOD`	Adverbial phrase modifier
`AUXCAUS`	Causative auxiliary
`AUXVV`	Helper auxiliary
`DTMOD`	Rentaishi (Prenominal modifier)
`FOREIGN`	Foreign words
`KW`	Keyword
`LIST`	List for chains of comparable items
`NOMC`	Nominalized clause
`NOMCSUBJ`	Nominalized clausal subject
`NOMCSUBJPASS`	Nominalized clausal passive
`NUMC`	Compound of numeric modifier
`COP`	Copula
`DISLOCATED`	Dislocated relation (for fronted/topicalized elements)
`ASP`	Aspect marker
`GMOD`	Genitive modifier
`GOBJ`	Genitive object
`INFMOD`	Infinitival modifier
`MES`	Measure
`NCOMP`	Nominal complement of a noun

Document

########################################################## # Represents the input to API methods.

Fields
`content`	`string` The content of the input in string format. Cloud audit logging exempt since it is based on user data.
`gcsContentUri`	`string` The Google Cloud Storage URI where the file content is located. This URI must be of the form: gs://bucket_name/object_name. For more details, see https://cloud.google.com/storage/docs/reference-uris. NOTE: Cloud Storage object versioning is not supported.
`language`	`string` The language of the document (if not specified, the language is automatically detected). Both ISO and BCP-47 language codes are accepted. Language Support lists currently supported languages for each API method. If the language (either specified by the caller or automatically detected) is not supported by the called API method, an `INVALID_ARGUMENT` error is returned.
`type`	`enum` Required. If the type is not set or is `TYPE_UNSPECIFIED`, returns an `INVALID_ARGUMENT` error.
Enum type. Can be one of the following:
`TYPE_UNSPECIFIED`	The content type is not specified.
`PLAIN_TEXT`	Plain text
`HTML`	HTML

Entity

Represents a phrase in the text that is a known entity, such as a person, an organization, or location. The API associates information, such as salience and mentions, with entities.

Fields
`mentions[]`	`object (EntityMention)` The mentions of this entity in the input document. The API currently supports proper noun mentions.
`metadata`	`map (key: string, value: string)` Metadata associated with the entity. For most entity types, the metadata is a Wikipedia URL (`wikipedia_url`) and Knowledge Graph MID (`mid`), if they are available. For the metadata associated with other entity types, see the Type table below.
`name`	`string` The representative name for the entity.
`salience`	`number (float format)` The salience score associated with the entity in the [0, 1.0] range. The salience score for an entity provides information about the importance or centrality of that entity to the entire document text. Scores closer to 0 are less salient, while scores closer to 1.0 are highly salient.
`sentiment`	`object (Sentiment)` For calls to AnalyzeEntitySentiment or if AnnotateTextRequest.Features.extract_entity_sentiment is set to true, this field will contain the aggregate sentiment expressed for this entity in the provided document.
`type`	`enum` The entity type.
Enum type. Can be one of the following:
`UNKNOWN`	Unknown
`PERSON`	Person
`LOCATION`	Location
`ORGANIZATION`	Organization
`EVENT`	Event
`WORK_OF_ART`	Artwork
`CONSUMER_GOOD`	Consumer product
`OTHER`	Other types of entities
`PHONE_NUMBER`	Phone number The metadata lists the phone number, formatted according to local convention, plus whichever additional elements appear in the text: * `number` - the actual number, broken down into sections as per local convention * `national_prefix` - country code, if detected * `area_code` - region or area code, if detected * `extension` - phone extension (to be dialed after connection), if detected
`ADDRESS`	Address The metadata identifies the street number and locality plus whichever additional elements appear in the text: * `street_number` - street number * `locality` - city or town * `street_name` - street/route name, if detected * `postal_code` - postal code, if detected * `country` - country, if detected< * `broad_region` - administrative area, such as the state, if detected * `narrow_region` - smaller administrative area, such as county, if detected * `sublocality` - used in Asian addresses to demark a district within a city, if detected
`DATE`	Date The metadata identifies the components of the date: * `year` - four digit year, if detected * `month` - two digit month number, if detected * `day` - two digit day number, if detected
`NUMBER`	Number The metadata is the number itself.
`PRICE`	Price The metadata identifies the `value` and `currency`.

EntityMention

Represents a mention for an entity in the text. Currently, proper noun mentions are supported.

Fields
`sentiment`	`object (Sentiment)` For calls to AnalyzeEntitySentiment or if AnnotateTextRequest.Features.extract_entity_sentiment is set to true, this field will contain the sentiment expressed for this mention of the entity in the provided document.
`text`	`object (TextSpan)` The mention text.
`type`	`enum` The type of the entity mention.
Enum type. Can be one of the following:
`TYPE_UNKNOWN`	Unknown
`PROPER`	Proper name
`COMMON`	Common noun (or noun compound)

Features

All available features for sentiment, syntax, and semantic analysis. Setting each one to true will enable that specific analysis for the input.

Fields
`classifyText`	`boolean` Classify the full document into categories.
`extractDocumentSentiment`	`boolean` Extract document-level sentiment.
`extractEntities`	`boolean` Extract entities.
`extractEntitySentiment`	`boolean` Extract entities and their associated sentiment.
`extractSyntax`	`boolean` Extract syntax information.

PartOfSpeech

Represents part of speech information for a token. Parts of speech are as defined in http://www.lrec-conf.org/proceedings/lrec2012/pdf/274_Paper.pdf

Fields
`aspect`	`enum` The grammatical aspect.
Enum type. Can be one of the following:
`ASPECT_UNKNOWN`	Aspect is not applicable in the analyzed language or is not predicted.
`PERFECTIVE`	Perfective
`IMPERFECTIVE`	Imperfective
`PROGRESSIVE`	Progressive

`case`	`enum` The grammatical case.
Enum type. Can be one of the following:
`CASE_UNKNOWN`	Case is not applicable in the analyzed language or is not predicted.
`ACCUSATIVE`	Accusative
`ADVERBIAL`	Adverbial
`COMPLEMENTIVE`	Complementive
`DATIVE`	Dative
`GENITIVE`	Genitive
`INSTRUMENTAL`	Instrumental
`LOCATIVE`	Locative
`NOMINATIVE`	Nominative
`OBLIQUE`	Oblique
`PARTITIVE`	Partitive
`PREPOSITIONAL`	Prepositional
`REFLEXIVE_CASE`	Reflexive
`RELATIVE_CASE`	Relative
`VOCATIVE`	Vocative

`form`	`enum` The grammatical form.
Enum type. Can be one of the following:
`FORM_UNKNOWN`	Form is not applicable in the analyzed language or is not predicted.
`ADNOMIAL`	Adnomial
`AUXILIARY`	Auxiliary
`COMPLEMENTIZER`	Complementizer
`FINAL_ENDING`	Final ending
`GERUND`	Gerund
`REALIS`	Realis
`IRREALIS`	Irrealis
`SHORT`	Short form
`LONG`	Long form
`ORDER`	Order form
`SPECIFIC`	Specific form

`gender`	`enum` The grammatical gender.
Enum type. Can be one of the following:
`GENDER_UNKNOWN`	Gender is not applicable in the analyzed language or is not predicted.
`FEMININE`	Feminine
`MASCULINE`	Masculine
`NEUTER`	Neuter

`mood`	`enum` The grammatical mood.
Enum type. Can be one of the following:
`MOOD_UNKNOWN`	Mood is not applicable in the analyzed language or is not predicted.
`CONDITIONAL_MOOD`	Conditional
`IMPERATIVE`	Imperative
`INDICATIVE`	Indicative
`INTERROGATIVE`	Interrogative
`JUSSIVE`	Jussive
`SUBJUNCTIVE`	Subjunctive

`number`	`enum` The grammatical number.
Enum type. Can be one of the following:
`NUMBER_UNKNOWN`	Number is not applicable in the analyzed language or is not predicted.
`SINGULAR`	Singular
`PLURAL`	Plural
`DUAL`	Dual

`person`	`enum` The grammatical person.
Enum type. Can be one of the following:
`PERSON_UNKNOWN`	Person is not applicable in the analyzed language or is not predicted.
`FIRST`	First
`SECOND`	Second
`THIRD`	Third
`REFLEXIVE_PERSON`	Reflexive

`proper`	`enum` The grammatical properness.
Enum type. Can be one of the following:
`PROPER_UNKNOWN`	Proper is not applicable in the analyzed language or is not predicted.
`PROPER`	Proper
`NOT_PROPER`	Not proper

`reciprocity`	`enum` The grammatical reciprocity.
Enum type. Can be one of the following:
`RECIPROCITY_UNKNOWN`	Reciprocity is not applicable in the analyzed language or is not predicted.
`RECIPROCAL`	Reciprocal
`NON_RECIPROCAL`	Non-reciprocal

`tag`	`enum` The part of speech tag.
Enum type. Can be one of the following:
`UNKNOWN`	Unknown
`ADJ`	Adjective
`ADP`	Adposition (preposition and postposition)
`ADV`	Adverb
`CONJ`	Conjunction
`DET`	Determiner
`NOUN`	Noun (common and proper)
`NUM`	Cardinal number
`PRON`	Pronoun
`PRT`	Particle or other function word
`PUNCT`	Punctuation
`VERB`	Verb (all tenses and modes)
`X`	Other: foreign words, typos, abbreviations
`AFFIX`	Affix

`tense`	`enum` The grammatical tense.
Enum type. Can be one of the following:
`TENSE_UNKNOWN`	Tense is not applicable in the analyzed language or is not predicted.
`CONDITIONAL_TENSE`	Conditional
`FUTURE`	Future
`PAST`	Past
`PRESENT`	Present
`IMPERFECT`	Imperfect
`PLUPERFECT`	Pluperfect

`voice`	`enum` The grammatical voice.
Enum type. Can be one of the following:
`VOICE_UNKNOWN`	Voice is not applicable in the analyzed language or is not predicted.
`ACTIVE`	Active
`CAUSATIVE`	Causative
`PASSIVE`	Passive

Sentence

Represents a sentence in the input document.

Fields

Fields
`sentiment`	`object (Sentiment)` For calls to AnalyzeSentiment or if AnnotateTextRequest.Features.extract_document_sentiment is set to true, this field will contain the sentiment for the sentence.
`text`	`object (TextSpan)` The sentence text.

sentiment

object (Sentiment)

For calls to AnalyzeSentiment or if AnnotateTextRequest.Features.extract_document_sentiment is set to true, this field will contain the sentiment for the sentence.

text

object (TextSpan)

The sentence text.

Sentiment

Represents the feeling associated with the entire text or entities in the text.

Fields

Fields
`magnitude`	`number (float format)` A non-negative number in the [0, +inf) range, which represents the absolute magnitude of sentiment regardless of score (positive or negative).
`score`	`number (float format)` Sentiment score between -1.0 (negative sentiment) and 1.0 (positive sentiment).

magnitude

number (float format)

A non-negative number in the [0, +inf) range, which represents the absolute magnitude of sentiment regardless of score (positive or negative).

score

number (float format)

Sentiment score between -1.0 (negative sentiment) and 1.0 (positive sentiment).

Status

The Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC. Each Status message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the API Design Guide.

Fields

Fields
`code`	`integer (int32 format)` The status code, which should be an enum value of google.rpc.Code.
`details[]`	`object` A list of messages that carry the error details. There is a common set of message types for APIs to use.
`message`	`string` A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

code

integer (int32 format)

The status code, which should be an enum value of google.rpc.Code.

details[]

object

A list of messages that carry the error details. There is a common set of message types for APIs to use.

message

string

A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

TextSpan

Represents an output piece of text.

Fields

Fields
`beginOffset`	`integer (int32 format)` The API calculates the beginning offset of the content in the original document according to the EncodingType specified in the API request.
`content`	`string` The content of the output text.

beginOffset

integer (int32 format)

The API calculates the beginning offset of the content in the original document according to the EncodingType specified in the API request.

content

string

The content of the output text.

Token

Represents the smallest syntactic building block of the text.

Fields
`dependencyEdge`	`object (DependencyEdge)` Dependency tree parse for this token.
`lemma`	`string` Lemma of the token.
`partOfSpeech`	`object (PartOfSpeech)` Parts of speech tag for this token.
`text`	`object (TextSpan)` The token text.