CLAIFeb 2, 2017

Multilingual and Cross-lingual Timeline Extraction

arXiv:1702.00700v110 citations
Originality Incremental advance
AI Analysis

This work addresses timeline extraction for multilingual and cross-lingual applications, representing an incremental advancement over existing tasks.

The paper tackles the problem of extracting ordered timelines of events from multilingual and cross-lingual data sources by developing deterministic algorithms that leverage implicit temporal relations and multilingual resources, resulting in a system that strongly outperforms the current state-of-the-art.

In this paper we present an approach to extract ordered timelines of events, their participants, locations and times from a set of multilingual and cross-lingual data sources. Based on the assumption that event-related information can be recovered from different documents written in different languages, we extend the Cross-document Event Ordering task presented at SemEval 2015 by specifying two new tasks for, respectively, Multilingual and Cross-lingual Timeline Extraction. We then develop three deterministic algorithms for timeline extraction based on two main ideas. First, we address implicit temporal relations at document level since explicit time-anchors are too scarce to build a wide coverage timeline extraction system. Second, we leverage several multilingual resources to obtain a single, inter-operable, semantic representation of events across documents and across languages. The result is a highly competitive system that strongly outperforms the current state-of-the-art. Nonetheless, further analysis of the results reveals that linking the event mentions with their target entities and time-anchors remains a difficult challenge. The systems, resources and scorers are freely available to facilitate its use and guarantee the reproducibility of results.

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