Learning to Identify Historical Figures for Timeline Creation from Wikipedia Articles

Abstract

Abstract. This paper addresses a central sub-task of timeline creation from historical Wikipedia articles: learning from text which of the person names in a textual article should appear in a timeline on the same topic. We first process hundreds of timelines written by human experts and related Wikipedia articles to construct a corpus that can be used to evaluate systems that create history timelines from text documents. We then use a set of features to train a classifier that predicts the most important person names, resulting in a clear improvement over a competitive baseline.

Euskarazko denbora-informazioaren tratamendu automatikoa TimeMLren eta HeidelTimeren bidez

“…HPn denbora-informazioa hainbat sistematan izan daiteke erabilgarria, hala nola kronologien sorrera automatikoan [1], gertaeren aurreikuspenean [2] eta etorkizunaren iragarpenean [3]. Horretarako, hiztunok denbora adierazteko erabiltzen ditugun egiturak identifikatu, normalizatu eta horien ezaugarriak azaleratu behar dira.…”

A Methodology for Evaluating Timeline Generation Algorithms based on Deep Semantic Units

“…To find suitable historical articles for our corpus, we created the intersection of all Wikipedia articles whose title starts with "History of" with the articles in a large collection of timelines described by Bauer et al (2014). Articles with errors in their Wikitext were removed.…”

EusTimeML: A mark-up language for temporal information in Basque

“…Temporal information is an integral part of those areas as it conveys the information of what is narrated in text while providing information to arrange narratives along a temporal axis. This information is of utmost relevance to the development of automatic systems that benefit from knowing the chronological ordering of events in texts, such as chronology creation (Bauer et al 2015), event prediction (Radinsky and Horvitz 2013) and event forecasting systems (Kawai et al 2010), among others.…”