NDLTD logo NDLTD Union Catalog and Global ETD Search
Back to results

National University of Singapore

DOCUMENT-LEVEL RELATION EXTRACTION AND TEMPORAL REASONING WITH LARGE LANGUAGE MODELS

dc:creator TAN QINGYU
dc:date.issued2025

Abstract

dc:description.abstract

Large Language Models (LLMs) have become the backbone models for many natural language processing (NLP) tasks. In this thesis, we study the applications and limitations of LLMs in two aspects: (1) Document-level Relation Extraction (DocRE), and (2) Temporal Reasoning.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • TAN QINGYU

Subjects

dc:subject × 3

Rights

dc:rights
Licence

Chain of custody

source
Harvested from
National University of Singapore
Base URL
scholarbank.nus.edu.sg/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

TAN QINGYU. DOCUMENT-LEVEL RELATION EXTRACTION AND TEMPORAL REASONING WITH LARGE LANGUAGE MODELS. 2025.

More from National University of Singapore

  1. REGULATION OF INFLAMMATION AND METABOLISM BY INTERFERON REGULATORY FACTOR 3 AND MAP KINASE PHOSPHATASE 5 TANG PENG 2014
  2. AN EXPERIMENTAL AND NUMERICAL STUDY ON CAVITATION BUBBLE DYNAMICS AND ITS BIOMEDICAL APPLICATIONS GOH BING HUI, TERENCE 2014
  3. The Transition Probability of the Inhomogeneous q-TAZRP DAVID WAUGH 2015