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SPARQL-QA-v2 system for Knowledge Base Question Answering

EXPERT SYSTEMS WITH APPLICATIONS (2023)

A Hereditary Attentive Template-based Approach for Complex Knowledge Base Question Answering Systems

Jorao Gomes et al.

Summary: This study introduces a template matching approach for Complex KBQA systems utilizing Semantic Parsing and Neural Networks techniques. The results demonstrate that our approach outperforms other methods on multiple datasets.

EXPERT SYSTEMS WITH APPLICATIONS (2022)

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Article Computer Science, Theory & Methods

Neural machine translating from natural language to SPARQL

Xiaoyu Yin et al.

Summary: This paper evaluates the utilization of eight different Neural Machine Translation models for translating from natural language to the structured query language SPARQL, highlighting the importance of high-quantity and high-quality datasets. The results show the dominance of a Convolutional Neural Network-based architecture with a Bilingual Evaluation Understudy score of up to 98 and accuracy of up to 94%.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2021)

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Article Computer Science, Artificial Intelligence