Document Type
Journal Article
Publication Title
Expert Systems with Applications
Publisher
Elsevier
School
School of Science / ECU Security Research Institute
RAS ID
62103
Abstract
Extracting valuable insights from vast amounts of unstructured digital text presents significant challenges across diverse domains. This research addresses this challenge by proposing a novel pipeline-based system that generates domain-agnostic and task-agnostic text representations. The proposed approach leverages labeled property graphs (LPG) to encode contextual information, facilitating the integration of diverse linguistic elements into a unified representation. The proposed system enables efficient graph-based querying and manipulation by addressing the crucial aspect of comprehensive context modeling and fine-grained semantics. The effectiveness of the proposed system is demonstrated through the implementation of NLP components that operate on LPG-based representations. Additionally, the proposed approach introduces specialized patterns and algorithms to enhance specific NLP tasks, including nominal mention detection, named entity disambiguation, event enrichments, event participant detection, and temporal link detection. The evaluation of the proposed approach, using the MEANTIME corpus comprising manually annotated documents, provides encouraging results and valuable insights into the system's strengths. The proposed pipeline-based framework serves as a solid foundation for future research, aiming to refine and optimize LPG-based graph structures to generate comprehensive and semantically rich text representations, addressing the challenges associated with efficient information extraction and analysis in NLP.
DOI
10.1016/j.eswa.2023.122269
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
Hur, A., Janjua, N., & Ahmed, M. (2024). Unifying context with labeled property graph: A pipeline-based system for comprehensive text representation in NLP. Expert Systems with Applications, 239, article 122269. https://doi.org/10.1016/j.eswa.2023.122269