HMTL for NLP
GitHub
Named Entity Recognition
Entity Mention Detection
Relation Extraction
Coreference Resolution

Compare with CoreNLP’s results on the same query. Or compare with spaCy’s displaCy results on entity recognition.

This is a demo of HMTL for NLP, our new NLP multi-task model that reaches or beats the state-of-the-art on 4 distinct NLP tasks. The model combines Named Entity Recognition, Entity Mention Detection, Relation Extraction and Coreference Resolution. These 4 tasks are all fundamentals for NLP and NLU applications such as conversational agents. Moreover, these 4 tasks can benefit each other when trained together in a multi-task learning framework, a recent trend in NLP which has been driving a lot of top-notch research.

Our implementation is based on the AllenNLP library from the Allen Institute for Artificial Intelligence, and makes use of the ELMo embeddings. If you like this demo, please share it and tweet about it 💛!

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