# Multilingual and Cross-lingual Timeline Extraction

## TL;DR

This paper introduces a multilingual and cross-lingual timeline extraction approach that leverages deterministic algorithms and multilingual resources to identify ordered event timelines across diverse languages, outperforming previous methods.

## Contribution

It extends the Cross-document Event Ordering task by defining new multilingual and cross-lingual timeline extraction tasks and develops algorithms that handle implicit temporal relations and multilingual data.

## Key findings

- System outperforms state-of-the-art methods
- Effective handling of implicit temporal relations
- Resources and algorithms are publicly available

## Abstract

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.