Entity Typing with Triples Using Language Models

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

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  • University of Bonn
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Details

Original languageEnglish
Title of host publicationThe Semantic Web
Subtitle of host publicationESWC 2023 Satellite Events
EditorsCatia Pesquita, Hala Skaf-Molli, Vasilis Efthymiou, Sabrina Kirrane, Axel Ngonga, Diego Collarana, Renato Cerqueira, Mehwish Alam, Cassia Trojahn, Sven Hertling
PublisherSpringer Science and Business Media Deutschland GmbH
Pages169-173
Number of pages5
ISBN (electronic)978-3-031-43458-7
ISBN (print)9783031434570
Publication statusPublished - 21 Oct 2023
Event20th Extended Semantic Web Conference, ESWC 2023 - Hersonissos, Greece
Duration: 28 May 20231 Jun 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13998 LNCS
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Abstract

Entity Typing is the task of assigning a type to an entity in a knowledge graph. In this paper, we propose ETwT (Entity Typing with Triples), which leverages the triples of an entity, namely its label, description and the property labels used on it. We analyse which language models and classifiers are best suited to this input and compare ETwT’s performance on coarse-grained and fine-grained entity typing. Our evaluation demonstrates that ETwT is able to predict coarse-grained entity types with an F $$:1$$ score of 0.994, outperforming three baselines.

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Cite this

Entity Typing with Triples Using Language Models. / Riaz, Aniqa; Abdollahi, Sara; Gottschalk, Simon.
The Semantic Web: ESWC 2023 Satellite Events. ed. / Catia Pesquita; Hala Skaf-Molli; Vasilis Efthymiou; Sabrina Kirrane; Axel Ngonga; Diego Collarana; Renato Cerqueira; Mehwish Alam; Cassia Trojahn; Sven Hertling. Springer Science and Business Media Deutschland GmbH, 2023. p. 169-173 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13998 LNCS).

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Riaz, A, Abdollahi, S & Gottschalk, S 2023, Entity Typing with Triples Using Language Models. in C Pesquita, H Skaf-Molli, V Efthymiou, S Kirrane, A Ngonga, D Collarana, R Cerqueira, M Alam, C Trojahn & S Hertling (eds), The Semantic Web: ESWC 2023 Satellite Events. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13998 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 169-173, 20th Extended Semantic Web Conference, ESWC 2023, Hersonissos, Greece, 28 May 2023. https://doi.org/10.1007/978-3-031-43458-7_32
Riaz, A., Abdollahi, S., & Gottschalk, S. (2023). Entity Typing with Triples Using Language Models. In C. Pesquita, H. Skaf-Molli, V. Efthymiou, S. Kirrane, A. Ngonga, D. Collarana, R. Cerqueira, M. Alam, C. Trojahn, & S. Hertling (Eds.), The Semantic Web: ESWC 2023 Satellite Events (pp. 169-173). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13998 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-43458-7_32
Riaz A, Abdollahi S, Gottschalk S. Entity Typing with Triples Using Language Models. In Pesquita C, Skaf-Molli H, Efthymiou V, Kirrane S, Ngonga A, Collarana D, Cerqueira R, Alam M, Trojahn C, Hertling S, editors, The Semantic Web: ESWC 2023 Satellite Events. Springer Science and Business Media Deutschland GmbH. 2023. p. 169-173. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-43458-7_32
Riaz, Aniqa ; Abdollahi, Sara ; Gottschalk, Simon. / Entity Typing with Triples Using Language Models. The Semantic Web: ESWC 2023 Satellite Events. editor / Catia Pesquita ; Hala Skaf-Molli ; Vasilis Efthymiou ; Sabrina Kirrane ; Axel Ngonga ; Diego Collarana ; Renato Cerqueira ; Mehwish Alam ; Cassia Trojahn ; Sven Hertling. Springer Science and Business Media Deutschland GmbH, 2023. pp. 169-173 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Download
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title = "Entity Typing with Triples Using Language Models",
abstract = "Entity Typing is the task of assigning a type to an entity in a knowledge graph. In this paper, we propose ETwT (Entity Typing with Triples), which leverages the triples of an entity, namely its label, description and the property labels used on it. We analyse which language models and classifiers are best suited to this input and compare ETwT{\textquoteright}s performance on coarse-grained and fine-grained entity typing. Our evaluation demonstrates that ETwT is able to predict coarse-grained entity types with an F $$:1$$ score of 0.994, outperforming three baselines.",
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AU - Riaz, Aniqa

AU - Abdollahi, Sara

AU - Gottschalk, Simon

N1 - Funding Information: This work was partially funded the Federal Ministry for Economic Affairs and Climate Action (BMWK), Germany (“ATTENTION!”, 01MJ22012D).

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