Running analysis jobs using the console - Amazon Comprehend

Running analysis jobs using the console

You can use the Amazon Comprehend console to create and manage asynchronous analysis jobs. Your job analyzes documents stored in Amazon S3 to find entities such as events, phrases, primary language, sentiment, or personally identifiable information (PII).

To create an analysis job

  1. Sign in to the AWS Management Console and open the Amazon Comprehend console.

  2. From the left menu, choose Analysis jobs and then choose Create job.

  3. Under Job settings, give the analysis job a unique name.

  4. For Analysis type, choose one of the Built-in analysis types.

    If you choose Primary langugage, Personally identifiable information (PII), or Topic modeling, you can skip the next step.

  5. Depending on the Analysis type that you choose, the console displays one or more of the following additional fields:

    • Language is required for all built-in analysis types except Primary langugage and Topic modeling.

      Choose the language of your input documents.

    • Target event types is required for the Events analysis type.

      Select the types of events to detect in your input documents. For more information about supported event types, see Event types.

    • PII detection settings is required for the PII analysis type.

      Select the output mode. For more information about PII detection settings, see Detecting PII entities.

  6. Under Input data, specify where the input documents are located in Amazon S3:

    • To analyze your own documents, choose My documents, and choose Browse S3 to provide the path to the bucket or folder that contains your files.

    • To analyze samples that are provided by Amazon Comprehend, choose Example documents. In this case, Amazon Comprehend uses a bucket that is managed by AWS, and you don't specify the location.

  7. (Optional) For Input format, specify one of the following formats for your input files:

    • One document per file – Each file contains one input document. This is best for collections of large documents.

    • One document per line – The input is one or more files. Each line in a file is considered a document. This is best for short documents, such as social media postings. Each line must end with a line feed (LF, \n), a carriage return (CR, \r), or both (CRLF, \r\n). You can't use the UTF-8 line separator (u+2028) to end a line.

  8. Under Output data, choose Browse S3. Choose the Amazon S3 bucket or folder where you want Amazon Comprehend to write the output data that is produced by the analysis.

  9. (Optional) To encrypt the output result from your job, choose Encryption. Then, choose whether to use a KMS key associated with the current account or one from another account:

    • If you are using a key associated with the current account, choose the key alias or ID for KMS key ID.

    • If you are using a key associated with a different account, enter the ARN for the key alias or ID under KMS key ID.

      Note

      For more information on creating and using KMS keys and the associated encryption, see Key management service (KMS).

  10. Under Access permissions, provide an IAM role that:

    • Grants read access to the Amazon S3 location of your input documents.

    • Grants write access to the Amazon S3 location of your output documents.

    • Includes a trust policy that allows the comprehend.amazonaws.com service principal to assume the role and gain its permissions.

    If you don't already have an IAM role with these permissions and an appropriate trust policy, choose Create an IAM role to create one.

  11. When you have finished filling out the form, choose Create job to create and start the topic detection job.

The new job appears in the job list with the status field showing the status of the job. The field can be IN_PROGRESS for a job that is processing, COMPLETED for a job that has finished successfully, and FAILED for a job that has an error. You can click on a job to get more information about the job, including any error messages.

When the job is completed, Amazon Comprehend stores the analysis results in the output Amazon S3 location that you specified for the job. For a description of the analysis results for each insight type, see Insights.