name : start-targeted-sentiment-detection-job.rst **To start an asynchronous targeted sentiment analysis job** The following ``start-targeted-sentiment-detection-job`` example starts an asynchronous targeted sentiment analysis detection job for all files located at the address specified by the ``--input-data-config`` tag. The S3 bucket folder in this example contains ``SampleMovieReview1.txt``, ``SampleMovieReview2.txt``, and ``SampleMovieReview3.txt``. When the job is complete, ``output.tar.gz`` is placed at the location specified by the ``--output-data-config`` tag. ``output.tar.gz`` contains the files ``SampleMovieReview1.txt.out``, ``SampleMovieReview2.txt.out``, and ``SampleMovieReview3.txt.out``, which each contain all of the named entities and associated sentiments for a single input text file. :: aws comprehend start-targeted-sentiment-detection-job \ --job-name targeted_movie_review_analysis1 \ --language-code en \ --input-data-config "S3Uri=s3://amzn-s3-demo-bucket/MovieData" \ --output-data-config "S3Uri=s3://amzn-s3-demo-destination-bucket/testfolder/" \ --data-access-role-arn arn:aws:iam::111122223333:role/service-role/AmazonComprehendServiceRole-example-role Contents of ``SampleMovieReview1.txt``:: "The film, AnyMovie, is fairly predictable and just okay." Contents of ``SampleMovieReview2.txt``:: "AnyMovie is the essential sci-fi film that I grew up watching when I was a kid. I highly recommend this movie." Contents of ``SampleMovieReview3.txt``:: "Don't get fooled by the 'awards' for AnyMovie. All parts of the film were poorly stolen from other modern directors." Output:: { "JobId": "0b5001e25f62ebb40631a9a1a7fde7b3", "JobArn": "arn:aws:comprehend:us-west-2:111122223333:targeted-sentiment-detection-job/0b5001e25f62ebb40631a9a1a7fde7b3", "JobStatus": "SUBMITTED" } Contents of ``SampleMovieReview1.txt.out`` with line indents for readability:: { "Entities": [ { "DescriptiveMentionIndex": [ 0 ], "Mentions": [ { "BeginOffset": 4, "EndOffset": 8, "Score": 0.994972, "GroupScore": 1, "Text": "film", "Type": "MOVIE", "MentionSentiment": { "Sentiment": "NEUTRAL", "SentimentScore": { "Mixed": 0, "Negative": 0, "Neutral": 1, "Positive": 0 } } } ] }, { "DescriptiveMentionIndex": [ 0 ], "Mentions": [ { "BeginOffset": 10, "EndOffset": 18, "Score": 0.631368, "GroupScore": 1, "Text": "AnyMovie", "Type": "ORGANIZATION", "MentionSentiment": { "Sentiment": "POSITIVE", "SentimentScore": { "Mixed": 0.001729, "Negative": 0.000001, "Neutral": 0.000318, "Positive": 0.997952 } } } ] } ], "File": "SampleMovieReview1.txt", "Line": 0 } Contents of ``SampleMovieReview2.txt.out`` line indents for readability:: { "Entities": [ { "DescriptiveMentionIndex": [ 0 ], "Mentions": [ { "BeginOffset": 0, "EndOffset": 8, "Score": 0.854024, "GroupScore": 1, "Text": "AnyMovie", "Type": "MOVIE", "MentionSentiment": { "Sentiment": "POSITIVE", "SentimentScore": { "Mixed": 0, "Negative": 0, "Neutral": 0.000007, "Positive": 0.999993 } } }, { "BeginOffset": 104, "EndOffset": 109, "Score": 0.999129, "GroupScore": 0.502937, "Text": "movie", "Type": "MOVIE", "MentionSentiment": { "Sentiment": "POSITIVE", "SentimentScore": { "Mixed": 0, "Negative": 0, "Neutral": 0, "Positive": 1 } } }, { "BeginOffset": 33, "EndOffset": 37, "Score": 0.999823, "GroupScore": 0.999252, "Text": "film", "Type": "MOVIE", "MentionSentiment": { "Sentiment": "POSITIVE", "SentimentScore": { "Mixed": 0, "Negative": 0, "Neutral": 0.000001, "Positive": 0.999999 } } } ] }, { "DescriptiveMentionIndex": [ 0, 1, 2 ], "Mentions": [ { "BeginOffset": 43, "EndOffset": 44, "Score": 0.999997, "GroupScore": 1, "Text": "I", "Type": "PERSON", "MentionSentiment": { "Sentiment": "NEUTRAL", "SentimentScore": { "Mixed": 0, "Negative": 0, "Neutral": 1, "Positive": 0 } } }, { "BeginOffset": 80, "EndOffset": 81, "Score": 0.999996, "GroupScore": 0.52523, "Text": "I", "Type": "PERSON", "MentionSentiment": { "Sentiment": "NEUTRAL", "SentimentScore": { "Mixed": 0, "Negative": 0, "Neutral": 1, "Positive": 0 } } }, { "BeginOffset": 67, "EndOffset": 68, "Score": 0.999994, "GroupScore": 0.999499, "Text": "I", "Type": "PERSON", "MentionSentiment": { "Sentiment": "NEUTRAL", "SentimentScore": { "Mixed": 0, "Negative": 0, "Neutral": 1, "Positive": 0 } } } ] }, { "DescriptiveMentionIndex": [ 0 ], "Mentions": [ { "BeginOffset": 75, "EndOffset": 78, "Score": 0.999978, "GroupScore": 1, "Text": "kid", "Type": "PERSON", "MentionSentiment": { "Sentiment": "NEUTRAL", "SentimentScore": { "Mixed": 0, "Negative": 0, "Neutral": 1, "Positive": 0 } } } ] } ], "File": "SampleMovieReview2.txt", "Line": 0 } Contents of ``SampleMovieReview3.txt.out`` with line indents for readibility:: { "Entities": [ { "DescriptiveMentionIndex": [ 1 ], "Mentions": [ { "BeginOffset": 64, "EndOffset": 68, "Score": 0.992953, "GroupScore": 0.999814, "Text": "film", "Type": "MOVIE", "MentionSentiment": { "Sentiment": "NEUTRAL", "SentimentScore": { "Mixed": 0.000004, "Negative": 0.010425, "Neutral": 0.989543, "Positive": 0.000027 } } }, { "BeginOffset": 37, "EndOffset": 45, "Score": 0.999782, "GroupScore": 1, "Text": "AnyMovie", "Type": "ORGANIZATION", "MentionSentiment": { "Sentiment": "POSITIVE", "SentimentScore": { "Mixed": 0.000095, "Negative": 0.039847, "Neutral": 0.000673, "Positive": 0.959384 } } } ] }, { "DescriptiveMentionIndex": [ 0 ], "Mentions": [ { "BeginOffset": 47, "EndOffset": 50, "Score": 0.999991, "GroupScore": 1, "Text": "All", "Type": "QUANTITY", "MentionSentiment": { "Sentiment": "NEUTRAL", "SentimentScore": { "Mixed": 0.000001, "Negative": 0.000001, "Neutral": 0.999998, "Positive": 0 } } } ] }, { "DescriptiveMentionIndex": [ 0 ], "Mentions": [ { "BeginOffset": 106, "EndOffset": 115, "Score": 0.542083, "GroupScore": 1, "Text": "directors", "Type": "PERSON", "MentionSentiment": { "Sentiment": "NEUTRAL", "SentimentScore": { "Mixed": 0, "Negative": 0, "Neutral": 1, "Positive": 0 } } } ] } ], "File": "SampleMovieReview3.txt", "Line": 0 } For more information, see `Async analysis for Amazon Comprehend insights <https://docs.aws.amazon.com/comprehend/latest/dg/api-async-insights.html>`__ in the *Amazon Comprehend Developer Guide*.