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Knowledge and Information Systems

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03.01.2022 | Regular Paper

Named entity disambiguation in short texts over knowledge graphs

verfasst von: Wissem Bouarroudj, Zizette Boufaida, Ladjel Bellatreche

Erschienen in: Knowledge and Information Systems | Ausgabe 2/2022

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Abstract

The ever-growing usage of knowledge graphs (KGs) positions named entity disambiguation (NED) at the heart of designing accurate KG-driven systems such as query answering systems (QAS). According to the current research, most studies dealing with NED on KGs involve long texts, which is not the case of short text fragments, identified by their limited contexts. The accuracy of QASs strongly depends on the management of such short text. This limitation motivates this paper, which studies the NED problem on KGs, involving only short texts. First, we propose a NED approach including the following steps: (i) context expansion using WordNet to measure its similarity to the resource context. (ii) Exploiting coherence between entities in queries that contain more than one entity, such as “Is Michelle Obama the wife of Barack Obama?”. (iii) Taking into account the relations between words to calculate their similarity with the properties of a resource. (iv) the use of syntactic features. The NED solution approach is compared to state-of-the-art approaches using five datasets. The experimental results show that our approach outperforms these systems by 27% in the F-measure. A system called Welink, implementing our proposal, is available on GitHub, and it is also accessible via a REST API.

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Titel: Named entity disambiguation in short texts over knowledge graphs
verfasst von: Wissem Bouarroudj
Zizette Boufaida
Ladjel Bellatreche
Publikationsdatum: 03.01.2022
Verlag: Springer London
Erschienen in: Knowledge and Information Systems / Ausgabe 2/2022
Print ISSN: 0219-1377
Elektronische ISSN: 0219-3116
DOI: https://doi.org/10.1007/s10115-021-01642-9

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