Multilingual Event Linking to W ikidata (2022)

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.

## introduction language grounding refers to linking concepts (e.g., events/entities) to a context (e.g., a knowledge base) @xcite . knowledge base (kb) grounding is a key component of information extraction stack and is well-studied for linking entity references to kbs like wikipedia @xcite . in this work, we present a new multilingual task that involves linking event references to wikidata kb. 2 event linking differs from entity's as it involves taking into account the event participants as well as 1 https://github.com/adithya7/xlel-wd 2 www.wikidata.org its temporal and spatial attributes. @xcite defines event linking as connecting event references from news articles to a news archive consisting of first reports of the events. similar to entities, event linking is typically restricted to prominent or report-worthy events. in this work, we use a subset of wikidata as our event kb and link mentions from wikipedia/wikinews articles. 3 figure 1 illustrates our event linking methodology. event linking is closely related to the more commonly studied task of cross-document event coreference (cdec). the goal in cdec is to understand the identity relationship between event mentions. this identity is often complicated by subevent and membership relations among events @xcite . @xcite proposed event linking as an alternative to coreference that helps ground report-worthy events to a kb. they showed linking helps avoid the traditional bottlenecks seen with the event coreference task. we postulate linking to be a complementary task to coreference, where the first mention of an event in a document is typically linked or grounded to the kb and its relationship with the rest of the mentions from the document is captured via coreference. additionally, due to computational constraints, coreference resolution is often restricted to a small batch of documents. grounding, however, can be performed efficiently using dense retrieval methods @xcite and is scalable to any large multi-document corpora. grounding event references to a kb has many downstream applications. first, event identity encompasses multiple aspects such as spatio-temporal context and participants. these aspects typically spread across many documents, and kb grounding helps construct a shared global account for each event. second, grounding is a complementary task to coreference. in contrast to coreference, aliaksandra herasimenia est une nageuse biélorusse en activité spécialiste des épreuves de sprint en nage libre et en dos. ... multiple médaillée au niveau planétaire et continental, elle décroche en 2010 son premier titre international majeur lors des championnats d'europe de budapest, sur dos. ## related work our focus task of multilingual event linking shares resemblance with entity/event linking, entity/event coreference and other multilingual nlp tasks. ## modeling in this section, we present our systems for multilingual and crosslingual event linking to wikidata. we follow the entity linking system blink @xcite to adapt a retrieve and rank approach. given a mention, we first use a bert-based biencoder to retrieve top-k events from the candidate pool. then, we use a crossencoder to rerank these top-k candidates and identify the best event label. additionally, following the baselines from entity linking literature, we also experiment with bm25 as a candidate retrieval method. ## conclusion & future work we present the task of multilingual event linking to wikidata. to support this task, we first compile 21 for more detailed examples, refer to a dictionary of events from wikidata using temporal and spatial properties. we prepare descriptions for these events from multilingual wikipedia pages. we then identify a large collection of inlinks from various language wikipedia. depending on the language of event description, we present two variants of the task, multilingual (lg lg) and crosslingual (lg en). furthermore, to test crossdomain generalization we create a small evaluation set based on wikinews articles. our results using a retrieve+rank approach indicate that the crosslingual task is more challenging than the multilingual. event linking task has multiple interesting future directions. first, the wikidata-based event dictionary can be expanded to include hierarchical event structures (figure 2 ). since events are inherently hierarchical, this will present a more realistic challenge for the linking systems. second, mention coverage of our dataset can be expanded to include more verbal events. third, event linking systems can be improved with better temporal reasoning and improved handling of temporal and spatial expressions. fourth, the wikidata-based event dictionary can be expanded to include events that do not contain any english wikipedia descriptions.