Recognize entities

  • 4 minutes

Named entity recognition is a capability offered by Azure AI Language. It identifies and categorizes entities in unstructured text. It supports several categories of entity, including people, locations, events, products, organizations, etc.

There are several ways to call the named entity recognition API. Here, you use the azure_ai extension to recognize entities from the text in SQL queries.

Prerequisites

You need an Azure Database for PostgreSQL flexible server, with the azure_ai extension enabled and configured. You also need to authorize it with Azure Cognitive Services by setting a Language resource's key and endpoint.

Scenarios

Entity recognition is helpful in several domains, such as:

  • Search and indexing: Automatically build knowledge graphs and tag directories with identified entities.
  • Process automation: Automatically recognizes products and locations in unstructured text and routes them to customer support requests.
  • Market analysis: Measures most frequent entities and entity clusters from social media, customer reviews, support tickets, etc., to determine relevant topics and anticipate trends.

Using named entity recognition in SQL with Azure Cognitive Services

The Azure Database for PostgreSQL flexible server azure_ai extension provides user-defined functions (UDFs) to access AI capabilities from within SQL directly. The named entity recognition API is accessed with the azure_cognitive.recognize_entities function provided by azure_ai:

azure_cognitive.recognize_entities(
 text text,
 language text,
 timeout_ms integer DEFAULT 3600000,
 throw_on_error boolean DEFAULT true,
 disable_service_logs boolean DEFAULT false
)

The required parameters are text, the input, and language, the language in which the text is written. For example, en-us is US English, and fr is French. See language support for the complete list of available languages.

By default, entity recognition is stopped if it doesn't finish in 3,600,000 ms = 1 hour. You can customize this delay by changing timeout_ms.

If an error occurs, the default behavior is to throw an exception, resulting in a transaction rollback. You can disable this behavior by setting throw_on_error to false.

See the Azure Cognitive Services extension documentation for complete parameter documentation.

For example, invoking this query:

SELECT azure_cognitive.recognize_entities('For more information, see Cognitive Services Compliance and Privacy notes.', 'en-us');

Gives this result:

{"(\"Cognitive Services\",Skill,\"\",0.94)"}

Indicating the entity's name is "Cognitive Services," it's identified as a skill with a confidence score of 0.94.

You can use table columns for the input text:

SELECT description, azure_cognitive.recognize_entities(description, 'en-us')
FROM listings LIMIT 1;

Which returns:

 {"(house,Location,\"\",0.77)","(2013.,DateTime,DateRange,1)","(\"rooftop deck\",Location,\"\",0.88)","(\"lounge area\",Location,Structural,0.97)","(tub,Product,\"\",0.52)","
(5,Quantity,Number,0.8)","(bedrooms,Location,\"\",0.92)","(\"gourmet kitchen\",Location,\"\",0.87)","(2-3,Quantity,NumberRange,0.87)","(downtown,Location,Structural,0.8)","(\
"Queen Anne neighborhood\",Location,\"\",0.74)","(house,Location,\"\",0.96)","(barnwood,Product,\"\",0.61)","(steel,Product,\"\",0.73)","(concrete,Product,\"\",0.7)","(living
,Location,Structural,0.53)","(\"gourmet kitchen\",Location,\"\",0.7)","(kitchen,Location,\"\",0.77)","(reading,Skill,\"\",0.54)","(half,Quantity,Number,0.8)","(\"tv room\",Lo
cation,\"\",0.89)","(kitchen,Location,\"\",0.64)","(Fireplace,Product,\"\",0.91)","(sofa,Product,\"\",0.98)","(\"sitting area\",Location,\"\",0.93)","(\"Basement room\",Locat
ion,\"\",0.98)","(kids,PersonType,\"\",0.73)","(room,Location,Structural,0.78)","(patio,Location,Structural,0.75)","(basketball,Product,\"\",0.57)","(bedroom,Location,\"\",0.
8)","(basement,Location,\"\",0.94)","(\"concrete heated floors\",Product,\"\",0.95)","(\"queen sleeper sofa\",Product,\"\",0.86)","(tv,Location,\"\",0.54)","(basement,Locatio
n,\"\",0.92)","(room,Location,Structural,0.9)","(\"a second\",DateTime,Duration,0.85)","(family,PersonType,\"\",0.71)","(kids,PersonType,\"\",0.65)","(\"2nd floor\",Location,
Structural,0.56)","(4,Quantity,Number,0.8)","(bedrooms,Location,\"\",0.66)","(one,Quantity,Number,0.8)","(one,Quantity,Number,0.8)","(bedroom,Location,\"\",0.54)","(\"twin bu
nk beds\",Product,\"\",0.67)"}

Summary

Named entity recognition identifies and categorizes entities in input text. The Azure Cognitive Services language model does the heavy natural language processing. The azure_ai extension for Azure Database for PostgreSQL provides the azure_cognitive.recognize_entities API to access named entity recognition directly within SQL queries.