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A library for lightweight entity linking

Project description

Lightweight entity linking solution.

Please consider citing our works if you use code from this repository.

Main dependencies

  • python>=3.10
  • numpy==1.26.4
  • SPARQLWrapper==2.0.0
  • sentence_transformers==3.1.1
  • aiohttp==3.9.5
  • openai==1.54.2
  • beautifulsoup4==4.12.2
  • fake-useragent==1.5.1

Example & Usage

from linking import main

# Your API token which can be found here (https://github.com/marketplace/models/azure-openai/gpt-4o)
api_token = "YOUR_API_TOKEN"

main.EL(api_token=api_token, sentence="We used PCA and FA for our experiments.", mention="PCA", single="No", combination="No", disambiguation="No", embedding_model="Lajavaness/bilingual-embedding-large")
Wikipedia: https://en.wikipedia.org/wiki/Principal_component_analysis

Wikidata: https://www.wikidata.org/wiki/Q2873

DBpedia: http://dbpedia.org/resource/Principal_component_analysis

Execution Time: 00:00:18

Parameters

  • api_token: Your API token from here. (Required)
  • sentence: An english text. (Required)
  • mention: The mention you want to perform the linking, the mention should be from inside the provided sentence. (Required)
  • single: Usually used for difficult mentions, it searches each word of the mention individually, (deafult="No"), (Values: "Yes", "No"). (Optional)
  • combination: Usually used for difficult mentions, it makes combinations for each word of the mention, (deafult="No"), (Values: "Yes", "No"). (Optional)
  • embedding_model: A sentence-transformers model to perform text similarity, (deafault="Lajavaness/bilingual-embedding-large"), (Values: str of the name of any sentence-transformers model). (Optional)

Licence

This library is licensed under the CC-BY-NC 4.0 license.

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