Multilingual Event Linking to Wikidata
- URL: http://arxiv.org/abs/2204.06535v1
- Date: Wed, 13 Apr 2022 17:28:23 GMT
- Title: Multilingual Event Linking to Wikidata
- Authors: Adithya Pratapa, Rishubh Gupta, Teruko Mitamura
- Abstract summary: We propose two variants of the event linking task: 1) multilingual, where event descriptions are from the same language as the mention, and 2) crosslingual, where all event descriptions are in English.
We automatically compile a large-scale dataset for this task, comprising of 1.8M mentions across 44 languages referring to over 10.9K events from Wikidata.
- Score: 5.726712522440283
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We present a task of multilingual linking of events to a knowledge base. We
automatically compile a large-scale dataset for this task, comprising of 1.8M
mentions across 44 languages referring to over 10.9K events from Wikidata. We
propose two variants of the event linking task: 1) multilingual, where event
descriptions are from the same language as the mention, and 2) crosslingual,
where all event descriptions are in English. On the two proposed tasks, we
compare multiple event linking systems including BM25+ (Lv and Zhai, 2011) and
multilingual adaptations of the biencoder and crossencoder architectures from
BLINK (Wu et al., 2020). In our experiments on the two task variants, we find
both biencoder and crossencoder models significantly outperform the BM25+
baseline. Our results also indicate that the crosslingual task is in general
more challenging than the multilingual task. To test the out-of-domain
generalization of the proposed linking systems, we additionally create a
Wikinews-based evaluation set. We present qualitative analysis highlighting
various aspects captured by the proposed dataset, including the need for
temporal reasoning over context and tackling diverse event descriptions across
languages.
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