Shypd.aiThe largest open index of AI toolsW2NER is a Research & Education tool that provides source code for unified named entity recognition. It models NER as word-word relation classification, tackling flat, overlapped, and discontinuous NER tasks.
Trending
Also listed in
About
W2NER offers the source code for a novel approach to Unified Named Entity Recognition (NER), as presented in an AAAI 2022 paper. Unlike traditional methods that study flat, overlapped, and discontinuous NER individually, W2NER unifies these tasks by modeling them as word-word relation classification. The architecture effectively captures neighboring relations between entity words using Next-Neighboring-Word (NNW) and Tail-Head-Word-* (THW-*) relations. It employs a neural framework that treats unified NER as a 2D grid of word pairs, enhanced by multi-granularity 2D convolutions for refining grid representations. A co-predictor then reasons about word-word relations. The model has demonstrated state-of-the-art performance across 14 benchmark datasets, including both English and Chinese, for all three types of NER.
Capabilities
Pricing & Plans
Open Source
Free
FAQs
Trending
