A Factoid Question Answering System for Vietnamese
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Abstract (arXiv)
In this paper, we describe the development of an end-to-end factoid question answering system for the Vietnamese language. This system combines both statistical models and ontology-based methods in a chain of processing modules to provide high-quality mappings from natural language text to entities. We present the challenges in the development of such an intelligent user interface for an isolating language like Vietnamese and show that techniques developed for inflectional languages cannot be applied "as is". Our question answering system can answer a wide range of general knowledge questions with promising accuracy on a test set.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Mar 2018.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 1; 2024: 1.
5 papers.
- 2021PhoNLP: A joint multi-task learning model for Vietnamese part-of-speech tagging, named entity recognition and dependency parsingcited by 13
- 2022XLMRQA: Open-Domain Question Answering on Vietnamese Wikipedia-based Textual Knowledge Sourcecited by 2
- 2022AsPOS: Assamese Part of Speech Tagger using Deep Learning Approachcited by 2
- 2024Part-of-Speech Tagger for Bodo Language using Deep Learning approachcited by 2
- 2023Analyzing Vietnamese Legal Questions Using Deep Neural Networks with Biaffine Classifierscited by 0
- 2024Part-of-Speech Tagger for Bodo Language using Deep Learning approach6 Jan 2024
- 2023Analyzing Vietnamese Legal Questions Using Deep Neural Networks with Biaffine Classifiers27 Apr 2023
- 2022AsPOS: Assamese Part of Speech Tagger using Deep Learning Approach14 Dec 2022
- 2022XLMRQA: Open-Domain Question Answering on Vietnamese Wikipedia-based Textual Knowledge Source14 Apr 2022
- 2021PhoNLP: A joint multi-task learning model for Vietnamese part-of-speech tagging, named entity recognition and dependency parsing5 Jan 2021