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# coding=utf-8
# ------------------------------------
# Copyright (c) Microsoft.
# Licensed under the MIT License.
# ------------------------------------
"""
FILE: sample_recognize_linked_entities.py
DESCRIPTION:
This sample demonstrates how to run **entity linking** over text.
USAGE:
python sample_recognize_linked_entities.py
REQUIRED ENV VARS (for AAD / DefaultAzureCredential):
AZURE_TEXT_ENDPOINT
AZURE_CLIENT_ID
AZURE_TENANT_ID
AZURE_CLIENT_SECRET
NOTE:
If you want to use AzureKeyCredential instead, set:
- AZURE_TEXT_ENDPOINT
- AZURE_TEXT_KEY
"""
# [START recognize_linked_entities]
import os
from azure.identity import DefaultAzureCredential
from azure.ai.textanalytics import TextAnalysisClient
from azure.ai.textanalytics.models import (
MultiLanguageTextInput,
MultiLanguageInput,
TextEntityLinkingInput,
EntityLinkingActionContent,
AnalyzeTextEntityLinkingResult,
)
def sample_recognize_linked_entities():
# settings
endpoint = os.environ["AZURE_TEXT_ENDPOINT"]
credential = DefaultAzureCredential()
client = TextAnalysisClient(endpoint, credential=credential)
# input
text_a = (
"Microsoft was founded by Bill Gates with some friends he met at Harvard. One of his friends, Steve "
"Ballmer, eventually became CEO after Bill Gates as well. Steve Ballmer eventually stepped down as "
"CEO of Microsoft, and was succeeded by Satya Nadella. Microsoft originally moved its headquarters "
"to Bellevue, Washington in January 1979, but is now headquartered in Redmond"
)
body = TextEntityLinkingInput(
text_input=MultiLanguageTextInput(
multi_language_inputs=[MultiLanguageInput(id="A", text=text_a, language="en")]
),
action_content=EntityLinkingActionContent(model_version="latest"),
)
# Sync (non-LRO) call
result = client.analyze_text(body=body)
# Print results
if isinstance(result, AnalyzeTextEntityLinkingResult) and result.results and result.results.documents:
for doc in result.results.documents:
print(f"\nDocument ID: {doc.id}")
if not doc.entities:
print("No linked entities found for this document.")
continue
print("Linked Entities:")
for linked in doc.entities:
print(f" Name: {linked.name}")
print(f" Language: {linked.language}")
print(f" Data source: {linked.data_source}")
print(f" URL: {linked.url}")
print(f" ID: {linked.id}")
if linked.matches:
print(" Matches:")
for match in linked.matches:
print(f" Text: {match.text}")
print(f" Confidence score: {match.confidence_score}")
print(f" Offset: {match.offset}")
print(f" Length: {match.length}")
print()
else:
print("No documents in the response or unexpected result type.")
# [END recognize_linked_entities]
def main():
sample_recognize_linked_entities()
if __name__ == "__main__":
main()
|
