Affiliations: Ontology Engineering Group, Universidad Politécnica de Madrid, Spain
Correspondence:
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Corresponding author. María Navas-Loro, Ontology Engineering Group, Universidad Politécnica de Madrid. Campus de Montegancedo s/n. Boadilla del Monte 28660 (Madrid, Spain). E-mail: [email protected].
Abstract: Temporal information is crucial in knowledge extraction. Being able to locate events in a timeline is necessary to understand the narrative behind every text. To this aim, several temporal taggers have been proposed in literature –nevertheless, not all languages received the same attention. Most taggers work only for English texts, and not many have been developed for other languages. Also the scarcity of annotated corpora in other languages notably hinders the task. In this paper we present a new rule-based tagger called Annotador (Añotador in Spanish) able to process texts both in Spanish and English. Furthermore, a new corpus with more than 300 short texts containing common temporal expressions, called the HourGlass corpus, has been built in order to test it and to facilitate the development of new resources and tools. Professionals from different domains intervened in the gathering of the text, making it heterogeneous and easy to use thanks to the tags added to each entry. Finally, we analyzed main challenges in the time expression extraction task.
Keywords: Time expression, temporal tagger, Spanish language, NLP
