MatSciRE: Leveraging Pointer Networks to Automate Entity and Relation Extraction for Material Science Knowledge-base Construction

Material science literature is a rich source of factual information about various categories of entities (like materials and compositions) and various relations between these entities, such as conductivity, voltage, etc. Automatically extracting this information to generate a material science knowle...

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Published in:arXiv.org 2024-01
Main Authors: Mullick, Ankan, Ghosh, Akash, G Sai Chaitanya, Ghui, Samir, Nayak, Tapas, Lee, Seung-Cheol, Bhattacharjee, Satadeep, Goyal, Pawan
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Language:English
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Construction materials
Electric potential
Encoders-Decoders
Knowledge bases (artificial intelligence)
Voltage
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container_title arXiv.org
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creator Mullick, Ankan
Ghosh, Akash
G Sai Chaitanya
Ghui, Samir
Nayak, Tapas
Lee, Seung-Cheol
Bhattacharjee, Satadeep
Goyal, Pawan
description Material science literature is a rich source of factual information about various categories of entities (like materials and compositions) and various relations between these entities, such as conductivity, voltage, etc. Automatically extracting this information to generate a material science knowledge base is a challenging task. In this paper, we propose MatSciRE (Material Science Relation Extractor), a Pointer Network-based encoder-decoder framework, to jointly extract entities and relations from material science articles as a triplet (\(entity1, relation, entity2\)). Specifically, we target the battery materials and identify five relations to work on - conductivity, coulombic efficiency, capacity, voltage, and energy. Our proposed approach achieved a much better F1-score (0.771) than a previous attempt using ChemDataExtractor (0.716). The overall graphical framework of MatSciRE is shown in Fig 1. The material information is extracted from material science literature in the form of entity-relation triplets using MatSciRE.
doi_str_mv 10.48550/arxiv.2401.09839
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subjects Construction materials
Electric potential
Encoders-Decoders
Knowledge bases (artificial intelligence)
Voltage
title MatSciRE: Leveraging Pointer Networks to Automate Entity and Relation Extraction for Material Science Knowledge-base Construction
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