Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …

One strategy to recognize nested entities is to enumerate overlapped entity spans for
classification. However, current models independently verify every entity span, which …

Nested entities are observed in many domains due to their compositionality, which cannot
be easily recognized by the widely-used sequence labeling framework. A natural solution is …

Nested named entity recognition (NER) has been receiving increasing attention.
Recently,(Fu et al, 2021) adapt a span-based constituency parser to tackle nested NER …

Constituency parsing and nested named entity recognition (NER) are similar tasks since
they both aim to predict a collection of nested and non-crossing spans. In this work, we cast …

Named-entity recognition (NER) is one of the primary components in various natural
language processing tasks such as relation extraction, information retrieval, question …

Semantic role labeling (SRL) is a fundamental yet challenging task in the NLP community.
Recent works of SRL mainly fall into two lines: 1) BIO-based; 2) span-based. Despite …

Organizing all spans of a sentence into a two-dimensional (2D) representation unfolds a
semantic plane. It has the advantage to resolve nested semantic structures and to build …

Abstract While Named Entity Recognition (NER) is a widely studied task, making inferences
of entities with only a few labeled data has been challenging, especially for entities with …

Abstract Named Entity Recognition (NER) is generally regarded as a sequence labeling
task, and faces a serious problem when the named entities are nested. Span-based model …