The twenty-first century is presenting humankind with unprecedented environmental and
medical challenges. The ability to design novel proteins tailored for specific purposes would …

Named entity recognition (NER) is the task to identify mentions of rigid designators from text
belonging to predefined semantic types such as person, location, organization etc. NER …

Named Entity Recognition (NER) is a key component in NLP systems for question
answering, information retrieval, relation extraction, etc. NER systems have been studied …

Automatic knowledge graph construction aims at manufacturing structured human
knowledge. To this end, much effort has historically been spent extracting informative fact …

Abstract Named Entity Recognition (NER), one of the most fundamental problems in natural
language processing, seeks to identify the boundaries and types of entities with specific …

We study the open-domain named entity recognition (NER) problem under distant
supervision. The distant supervision, though does not require large amounts of manual …

In a surprising turn, Large Language Models (LLMs) together with a growing arsenal of
prompt-based heuristics now offer powerful off-the-shelf approaches providing few-shot …

In this study, we investigate the problem of named entity recognition for tweets. Named entity
recognition is an important task in natural language processing and has been carefully …

In this paper, we study Multimodal Named Entity Recognition (MNER) for social media posts.
Existing approaches for MNER mainly suffer from two drawbacks:(1) despite generating …

Clinical named entity recognition (CNER) is a fundamental step for many clinical Natural
Language Processing (NLP) systems, which aims to recognize and classify clinical entities …