ZhixiuYe/HSCRF-pytorch
ACL 2018: Hybrid semi-Markov CRF for Neural Sequence Labeling (http://aclweb.org/anthology/P18-2038)
This project helps natural language processing researchers evaluate and refine their models for tasks like Named Entity Recognition (NER). It takes text data, often used in benchmarks like CoNLL 2003, and outputs highly accurate predictions for identifying specific entities (like names, locations, organizations). Researchers and machine learning engineers working on improving text understanding systems would use this.
304 stars. No commits in the last 6 months.
Use this if you are an NLP researcher or ML engineer focused on achieving state-of-the-art performance in sequence labeling tasks like Named Entity Recognition.
Not ideal if you are looking for an out-of-the-box solution for general text analysis or if you are not comfortable working with research-level code and command-line execution.
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Python
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Jul 22, 2018
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