Detecting Entities in the Astrophysics Literature: A Comparison of Word-based and Span-based Entity Recognition Methods

NER refers to the task of identifying A large body of scientific literature is published mentions of different types of entities in in different domains, making it difficult for researchers free-text. Types of entities of interest depend on in their respective fields to find information the domain of the text; for example disease names or keep up-to-date. Automatic information in biomedical text (Islamaj Doğan et al., 2014; extraction, in particular Named Entity Recognition Dai, 2021) or numbers in finance (Loukas et al., (NER), is one of the core methods from the 2022). Methods to recognise such entities should NLP community to assist researchers. It finds also handle different types of the text, including mentions of entities of interest in a given text, both formal and informal text, such as social media such as in medicine (Rybinski et al., 2021), astronomy posts (Karimi et al., 2015; Basaldella et al., 2020).