bloomberg/entsum

Open Source / ENTSUM: A Data Set for Entity-Centric Extractive Summarization

29
/ 100
Experimental

This project helps natural language processing researchers and developers create specialized training datasets for entity-centric summarization models. It takes large text datasets, identifies specific entities, resolves duplicates, and outputs a refined dataset ready for training models like BERTSum or GSum. This is ideal for those building summarization systems that focus on extracting information around particular people, places, or organizations.

No commits in the last 6 months.

Use this if you need to prepare a dataset for training a summarization model that emphasizes specific entities within a document.

Not ideal if you are looking for a pre-trained summarization model or a general-purpose text summarization tool.

natural-language-processing text-summarization dataset-preparation entity-extraction machine-learning-research
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 6 / 25

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Stars

29

Forks

2

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

May 23, 2022

Commits (30d)

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