U-Alberta/wned

A sytem for Named Entity Disambiguation based on Random Walks and Learning to Rank.

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Experimental

When you have a piece of text that mentions people, places, or organizations, this project helps you automatically figure out exactly which real-world entity each mention refers to. For example, it can determine if "Apple" in a sentence means the fruit or the technology company. You provide text with marked names, and it outputs those names linked to their specific entries in a knowledge base like Wikipedia. This is for researchers and data scientists working with unstructured text data.

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Use this if you need to precisely identify and link named entities within large volumes of text to a structured knowledge base, resolving ambiguities like different entities having the same name.

Not ideal if you simply need to extract named entities without linking them to external knowledge base entries, or if you require real-time, low-latency processing for interactive applications.

natural-language-processing information-extraction knowledge-graph-population text-analytics
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 15 / 25

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Language

Java

License

Last pushed

Feb 26, 2022

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