%PDF- <> %âãÏÓ endobj 2 0 obj <> endobj 3 0 obj <>/ExtGState<>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/Annots[ 28 0 R 29 0 R] /MediaBox[ 0 0 595.5 842.25] /Contents 4 0 R/Group<>/Tabs/S>> endobj ºaâÚÎΞ-ÌE1ÍØÄ÷{òò2ÿ ÛÖ^ÔÀá TÎ{¦?§®¥kuµùÕ5sLOšuY>endobj 2 0 obj<>endobj 2 0 obj<>endobj 2 0 obj<>endobj 2 0 obj<> endobj 2 0 obj<>endobj 2 0 obj<>es 3 0 R>> endobj 2 0 obj<> ox[ 0.000000 0.000000 609.600000 935.600000]/Fi endobj 3 0 obj<> endobj 7 1 obj<>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI]>>/Subtype/Form>> stream
**Example 1: To detect entities directly from text** The following ``detect-entities-v2`` example shows the detected entities and labels them according to type, directly from input text. :: aws comprehendmedical detect-entities-v2 \ --text "Sleeping trouble on present dosage of Clonidine. Severe rash on face and leg, slightly itchy." Output:: { "Id": 0, "BeginOffset": 38, "EndOffset": 47, "Score": 0.9942955374717712, "Text": "Clonidine", "Category": "MEDICATION", "Type": "GENERIC_NAME", "Traits": [] }, For more information, see `Detect Entities Version 2 <https://docs.aws.amazon.com/comprehend/latest/dg/extracted-med-info-V2.html>`__ in the *Amazon Comprehend Medical Developer Guide*. **Example 2: To detect entities from a file path** The following ``detect-entities-v2`` example shows the detected entities and labels them according to type from a file path. :: aws comprehendmedical detect-entities-v2 \ --text file://medical_entities.txt Contents of ``medical_entities.txt``:: { "Sleeping trouble on present dosage of Clonidine. Severe rash on face and leg, slightly itchy." } Output:: { "Id": 0, "BeginOffset": 38, "EndOffset": 47, "Score": 0.9942955374717712, "Text": "Clonidine", "Category": "MEDICATION", "Type": "GENERIC_NAME", "Traits": [] }, For more information, see `Detect Entities Version 2 <https://docs.aws.amazon.com/comprehend/latest/dg/extracted-med-info-V2.html>`__ in the *Amazon Comprehend Medical Developer Guide*.