Comprehend / Client / detect_targeted_sentiment
detect_targeted_sentiment#
- Comprehend.Client.detect_targeted_sentiment(**kwargs)#
- Inspects the input text and returns a sentiment analysis for each entity identified in the text. - For more information about targeted sentiment, see Targeted sentiment in the Amazon Comprehend Developer Guide. - See also: AWS API Documentation - Request Syntax- response = client.detect_targeted_sentiment( Text='string', LanguageCode='en'|'es'|'fr'|'de'|'it'|'pt'|'ar'|'hi'|'ja'|'ko'|'zh'|'zh-TW' ) - Parameters:
- Text (string) – - [REQUIRED] - A UTF-8 text string. The maximum string length is 5 KB. 
- LanguageCode (string) – - [REQUIRED] - The language of the input documents. Currently, English is the only supported language. 
 
- Return type:
- dict 
- Returns:
- Response Syntax- { 'Entities': [ { 'DescriptiveMentionIndex': [ 123, ], 'Mentions': [ { 'Score': ..., 'GroupScore': ..., 'Text': 'string', 'Type': 'PERSON'|'LOCATION'|'ORGANIZATION'|'FACILITY'|'BRAND'|'COMMERCIAL_ITEM'|'MOVIE'|'MUSIC'|'BOOK'|'SOFTWARE'|'GAME'|'PERSONAL_TITLE'|'EVENT'|'DATE'|'QUANTITY'|'ATTRIBUTE'|'OTHER', 'MentionSentiment': { 'Sentiment': 'POSITIVE'|'NEGATIVE'|'NEUTRAL'|'MIXED', 'SentimentScore': { 'Positive': ..., 'Negative': ..., 'Neutral': ..., 'Mixed': ... } }, 'BeginOffset': 123, 'EndOffset': 123 }, ] }, ] } - Response Structure- (dict) – - Entities (list) – - Targeted sentiment analysis for each of the entities identified in the input text. - (dict) – - Information about one of the entities found by targeted sentiment analysis. - For more information about targeted sentiment, see Targeted sentiment in the Amazon Comprehend Developer Guide. - DescriptiveMentionIndex (list) – - One or more index into the Mentions array that provides the best name for the entity group. - (integer) – 
 
- Mentions (list) – - An array of mentions of the entity in the document. The array represents a co-reference group. See Co-reference group for an example. - (dict) – - Information about one mention of an entity. The mention information includes the location of the mention in the text and the sentiment of the mention. - For more information about targeted sentiment, see Targeted sentiment in the Amazon Comprehend Developer Guide. - Score (float) – - Model confidence that the entity is relevant. Value range is zero to one, where one is highest confidence. 
- GroupScore (float) – - The confidence that all the entities mentioned in the group relate to the same entity. 
- Text (string) – - The text in the document that identifies the entity. 
- Type (string) – - The type of the entity. Amazon Comprehend supports a variety of entity types. 
- MentionSentiment (dict) – - Contains the sentiment and sentiment score for the mention. - Sentiment (string) – - The sentiment of the mention. 
- SentimentScore (dict) – - Describes the level of confidence that Amazon Comprehend has in the accuracy of its detection of sentiments. - Positive (float) – - The level of confidence that Amazon Comprehend has in the accuracy of its detection of the - POSITIVEsentiment.
- Negative (float) – - The level of confidence that Amazon Comprehend has in the accuracy of its detection of the - NEGATIVEsentiment.
- Neutral (float) – - The level of confidence that Amazon Comprehend has in the accuracy of its detection of the - NEUTRALsentiment.
- Mixed (float) – - The level of confidence that Amazon Comprehend has in the accuracy of its detection of the - MIXEDsentiment.
 
 
- BeginOffset (integer) – - The offset into the document text where the mention begins. 
- EndOffset (integer) – - The offset into the document text where the mention ends. 
 
 
 
 
 
 
 - Exceptions- Comprehend.Client.exceptions.InvalidRequestException
- Comprehend.Client.exceptions.TextSizeLimitExceededException
- Comprehend.Client.exceptions.UnsupportedLanguageException
- Comprehend.Client.exceptions.InternalServerException