The Scholarly Question Answering over Linked Data (Scholarly QALD) at The International Semantic Web Conference (ISWC) 2023 challenge presents two sub-tasks to tackle question answering (QA) over knowledge graphs (KGs). We answer the KGQA over DBLP (DBLP-QUAD) task by proposing a neuro-symbolic (NS) framework based on PSYCHIC, an extractive QA model capable of identifying the query and entities related to a KG question. Our system achieved a F1 score of 00.18% on question answering and came in third place for entity linking (EL) with a score of 71.00%.
@article{arxiv.2310.12638,
title = {PSYCHIC: A Neuro-Symbolic Framework for Knowledge Graph Question-Answering Grounding},
author = {Hanna Abi Akl},
journal= {arXiv preprint arXiv:2310.12638},
year = {2023}
}
Comments
10 pages, 3 figures, 2 tables, accepted for the Scholarly-QALD challenge at the International Semantic Web Conference (ISWC) 2023