We introduce fastcoref, a python package for fast, accurate, and easy-to-use English coreference resolution. The package is pip-installable, and allows two modes: an accurate mode based on the LingMess architecture, providing state-of-the-art coreference accuracy, and a substantially faster model, F-coref, which is the focus of this work. F-coref allows to process 2.8K OntoNotes documents in 25 seconds on a V100 GPU (compared to 6 minutes for the LingMess model, and to 12 minutes of the popular AllenNLP coreference model) with only a modest drop in accuracy. The fast speed is achieved through a combination of distillation of a compact model from the LingMess model, and an efficient batching implementation using a technique we call leftover batching. Our code is available at https://github.com/shon-otmazgin/fastcoref
F-coref: Fast, Accurate and Easy to Use Coreference Resolution
A fast and accurate coreference resolution package, F-coref, achieves high performance with speed optimizations via model distillation and efficient batching.
- Year
- 2022
- Venue
- arXiv 2022
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- 3
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- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2209.04280v4ARXIV-DEFAULT
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