arXiv Open Access 2022

Integrating question answering and text-to-SQL in Portuguese

Marcos Menon José Marcelo Archanjo José Denis Deratani Mauá Fábio Gagliardi Cozman

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Abstrak

Deep learning transformers have drastically improved systems that automatically answer questions in natural language. However, different questions demand different answering techniques; here we propose, build and validate an architecture that integrates different modules to answer two distinct kinds of queries. Our architecture takes a free-form natural language text and classifies it to send it either to a Neural Question Answering Reasoner or a Natural Language parser to SQL. We implemented a complete system for the Portuguese language, using some of the main tools available for the language and translating training and testing datasets. Experiments show that our system selects the appropriate answering method with high accuracy (over 99\%), thus validating a modular question answering strategy.

Topik & Kata Kunci

cs.CL

Penulis (4)

Marcos Menon José

Marcelo Archanjo José

Denis Deratani Mauá

Fábio Gagliardi Cozman

Format Sitasi

APA MLA BibTeX

José, M.M., José, M.A., Mauá, D.D., Cozman, F.G. (2022). Integrating question answering and text-to-SQL in Portuguese. https://arxiv.org/abs/2202.04048

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓