Spaces:
No application file
No application file
| **To create a custom entity recognizer** | |
| The following ``create-entity-recognizer`` example begins the training process for a custom entity recognizer model. This example uses a CSV file containing training documents, ``raw_text.csv``, and a CSV entity list, ``entity_list.csv`` to train the model. | |
| ``entity-list.csv`` contains the following columns: text and type. :: | |
| aws comprehend create-entity-recognizer \ | |
| --recognizer-name example-entity-recognizer | |
| --data-access-role-arn arn:aws:iam::111122223333:role/service-role/AmazonComprehendServiceRole-example-role \ | |
| --input-data-config "EntityTypes=[{Type=DEVICE}],Documents={S3Uri=s3://DOC-EXAMPLE-BUCKET/trainingdata/raw_text.csv},EntityList={S3Uri=s3://DOC-EXAMPLE-BUCKET/trainingdata/entity_list.csv}" | |
| --language-code en | |
| Output:: | |
| { | |
| "EntityRecognizerArn": "arn:aws:comprehend:us-west-2:111122223333:example-entity-recognizer/entityrecognizer1" | |
| } | |
| For more information, see `Custom entity recognition <https://docs.aws.amazon.com/comprehend/latest/dg/custom-entity-recognition.html>`__ in the *Amazon Comprehend Developer Guide*. |