Year: 2024
Type: conference-paper
Abstract: One of the fundamental issues in natural language processing (NLP) is anaphora resolution, which is matching pronouns such as "he," "she," "it," or "they" to the right antecedents or referents in a text. Finding the words or phrases in the text that these pronouns are referring to is the main objective of anaphora resolution. Pro-nouns are frequently ambiguous, and several words or phrases in the text may potentially act as their antecedents, making this problem difficult to solve. To properly assign each pronoun to the appropriate referent, anaphora resolution necessitates taking the text's semantics and context into account. Many NLP applications, such as machine translation, text summarization, question answering, and coreference analysis, depend on successful anaphora resolution. The results demonstrate the effectiveness of our proposed methodology in resolving anaphoric references through salience in Magahi texts.
Authors: Sanjit Kumar, Lalita Kumari, Shweta Chandra, Garima Srivastava
Institutions: SRM Institute of Science and Technology, Amity University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4413915565