Babelscape/wikineural
Data and evaluation code for the paper WikiNEuRal: Combined Neural and Knowledge-based Silver Data Creation for Multilingual NER (EMNLP 2021).
This project helps anyone working with text in multiple languages to automatically identify and categorize important entities like people, organizations, and locations. It takes raw text in languages such as English, Spanish, German, or Russian and outputs the same text with these key entities highlighted and labeled. This is ideal for natural language processing (NLP) researchers, data scientists, or linguists building applications that need to understand content across different languages.
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Use this if you need high-quality training data or a pre-trained model for Named Entity Recognition (NER) across multiple languages, especially for applications like information extraction, content analysis, or search.
Not ideal if your primary need is for a simple, single-language NER solution where existing, smaller datasets are sufficient, or if you require fine-grained entity types beyond person, organization, location, and miscellaneous.
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Python
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Last pushed
Jan 27, 2023
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