TY - CHAP

T1 - Semantic Parsing for Knowledge Graph Question Answering with Large Language Models

AU - Banerjee, Debayan

N1 - Conference code: 20

PY - 2023

Y1 - 2023

N2 - This thesis explores the topic of Knowledge Graph Question Answering with a special emphasis on semantic parsing approaches, incorporating pre-trained text-to-text language models. We use the text generation ability of these models to convert natural language questions to logical forms. We test whether correct logical forms are being generated, and if not, how to mitigate the failure cases. As a second step, we try to make the same models generate additional information to aid the process of grounding of the logical forms to entities, relations and literals in the Knowledge Graph. In experiments conducted so far, we see encouraging results on both generation of base logical forms, and grounding them to the KG elements. At the same time, we discover failure cases prompting directions in future work (The author considers himself a ‘middle-stage’ Ph.D. candidate).

AB - This thesis explores the topic of Knowledge Graph Question Answering with a special emphasis on semantic parsing approaches, incorporating pre-trained text-to-text language models. We use the text generation ability of these models to convert natural language questions to logical forms. We test whether correct logical forms are being generated, and if not, how to mitigate the failure cases. As a second step, we try to make the same models generate additional information to aid the process of grounding of the logical forms to entities, relations and literals in the Knowledge Graph. In experiments conducted so far, we see encouraging results on both generation of base logical forms, and grounding them to the KG elements. At the same time, we discover failure cases prompting directions in future work (The author considers himself a ‘middle-stage’ Ph.D. candidate).

KW - Informatics

UR - http://www.scopus.com/inward/record.url?scp=85176013413&partnerID=8YFLogxK

UR - https://d-nb.info/1306843561

UR - https://www.mendeley.com/catalogue/28b64db7-d8bb-3600-8abf-1a65f182425d/

U2 - 10.1007/978-3-031-43458-7_42

DO - 10.1007/978-3-031-43458-7_42

M3 - Article in conference proceedings

AN - SCOPUS:85176013413

SN - 978-3-031-43457-0

T3 - Lecture Notes in Computer Science

SP - 234

EP - 243

BT - The Semantic Web

A2 - Pesquita, Catia

A2 - Skaf-Molli, Hala

A2 - Efthymiou, Vasilis

A2 - Kirrane, Sabrina

A2 - Ngonga, Axel

A2 - Collarana, Diego

A2 - Cerqueira, Renato

A2 - Alam, Mehwish

A2 - Trojahn, Cassia

A2 - Hertling, Sven

PB - Springer Science and Business Media Deutschland GmbH

CY - Cham

T2 - 20th International Conference on The Semantic Web - ESWC 2023

Y2 - 28 May 2023 through 1 June 2023

ER -