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 …

Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

Named entity recognition (NER) is a fundamental task in natural language processing.
Recent works treat named entity recognition as a reading comprehension task, constructing …

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 …

Recent work has shown that generation from a prompted or fine-tuned language model can
perform well at semantic parsing when the output is constrained to be a valid semantic …

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

Constituency parsing is a fundamental yet unsolved natural language processing task. In
this paper, we explore the potential of recent large language models (LLMs) that have …

Traditional methods to recognize named entities are conducted as sequence labelling or
span classification. They are usually implemented on a raw input without any cue about …

Extracting sentiment elements using pre-trained generative models has recently led to large
improvements in aspect-based sentiment analysis benchmarks. However, these models …

Nested named entities (nested NEs) refer to the situation where one named entity is
included or nested within another named entity, which cannot be recognized by the …