# A Factoid Question Answering System for Vietnamese

arXiv: https://arxiv.org/abs/1803.00712 · HTML: https://mlsanity.com/paper/1803.00712/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Mar 2018.

## Built on by (most cited first, 5 of 5)

- [PhoNLP: A joint multi-task learning model for Vietnamese part-of-speech tagging, named entity recognition and dependency parsing](https://mlsanity.com/paper/2101.01476/) (2021)
- [XLMRQA: Open-Domain Question Answering on Vietnamese Wikipedia-based Textual Knowledge Source](https://mlsanity.com/paper/2204.07002/) (2022)
- [AsPOS: Assamese Part of Speech Tagger using Deep Learning Approach](https://mlsanity.com/paper/2212.07043/) (2022)
- [Part-of-Speech Tagger for Bodo Language using Deep Learning approach](https://mlsanity.com/paper/2401.03175/) (2024)
- [Analyzing Vietnamese Legal Questions Using Deep Neural Networks with Biaffine Classifiers](https://mlsanity.com/paper/2304.14447/) (2023)

## 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.