**To detect the sentiment and each named entity for multiple input texts** The following ``batch-detect-targeted-sentiment`` example analyzes multiple input texts and returns the named entities along with the prevailing sentiment attached to each entity. The pre-trained model's confidence score is also output for each prediction. :: aws comprehend batch-detect-targeted-sentiment \ --language-code en \ --text-list "That movie was really boring, the original was way more entertaining" "The trail is extra beautiful today." "My meal was just okay." Output:: { "ResultList": [ { "Index": 0, "Entities": [ { "DescriptiveMentionIndex": [ 0 ], "Mentions": [ { "Score": 0.9999009966850281, "GroupScore": 1.0, "Text": "movie", "Type": "MOVIE", "MentionSentiment": { "Sentiment": "NEGATIVE", "SentimentScore": { "Positive": 0.13887299597263336, "Negative": 0.8057460188865662, "Neutral": 0.05525200068950653, "Mixed": 0.00012799999967683107 } }, "BeginOffset": 5, "EndOffset": 10 } ] }, { "DescriptiveMentionIndex": [ 0 ], "Mentions": [ { "Score": 0.9921110272407532, "GroupScore": 1.0, "Text": "original", "Type": "MOVIE", "MentionSentiment": { "Sentiment": "POSITIVE", "SentimentScore": { "Positive": 0.9999989867210388, "Negative": 9.999999974752427e-07, "Neutral": 0.0, "Mixed": 0.0 } }, "BeginOffset": 34, "EndOffset": 42 } ] } ] }, { "Index": 1, "Entities": [ { "DescriptiveMentionIndex": [ 0 ], "Mentions": [ { "Score": 0.7545599937438965, "GroupScore": 1.0, "Text": "trail", "Type": "OTHER", "MentionSentiment": { "Sentiment": "POSITIVE", "SentimentScore": { "Positive": 1.0, "Negative": 0.0, "Neutral": 0.0, "Mixed": 0.0 } }, "BeginOffset": 4, "EndOffset": 9 } ] }, { "DescriptiveMentionIndex": [ 0 ], "Mentions": [ { "Score": 0.9999960064888, "GroupScore": 1.0, "Text": "today", "Type": "DATE", "MentionSentiment": { "Sentiment": "NEUTRAL", "SentimentScore": { "Positive": 9.000000318337698e-06, "Negative": 1.9999999949504854e-06, "Neutral": 0.9999859929084778, "Mixed": 3.999999989900971e-06 } }, "BeginOffset": 29, "EndOffset": 34 } ] } ] }, { "Index": 2, "Entities": [ { "DescriptiveMentionIndex": [ 0 ], "Mentions": [ { "Score": 0.9999880194664001, "GroupScore": 1.0, "Text": "My", "Type": "PERSON", "MentionSentiment": { "Sentiment": "NEUTRAL", "SentimentScore": { "Positive": 0.0, "Negative": 0.0, "Neutral": 1.0, "Mixed": 0.0 } }, "BeginOffset": 0, "EndOffset": 2 } ] }, { "DescriptiveMentionIndex": [ 0 ], "Mentions": [ { "Score": 0.9995260238647461, "GroupScore": 1.0, "Text": "meal", "Type": "OTHER", "MentionSentiment": { "Sentiment": "NEUTRAL", "SentimentScore": { "Positive": 0.04695599898695946, "Negative": 0.003226999891921878, "Neutral": 0.6091709733009338, "Mixed": 0.34064599871635437 } }, "BeginOffset": 3, "EndOffset": 7 } ] } ] } ], "ErrorList": [] } For more information, see `Targeted Sentiment `__ in the *Amazon Comprehend Developer Guide*.