Within the general purpose of information extraction, detection of event descriptions is an important clue. A word refering to an event is more powerful than a single word, because it implies a location, a time, protagonists (persons, organizations\dots). However, if verbal designations of events are well studied and easier to detect than nominal ones, nominal designations do not claim as much definition effort and resources. In this work, we focus on nominals desribing events. As our application domain is information extraction, we follow a named entity approach to describe and annotate events. In this paper, we present a typology and annotation guidelines for event nominals annotation. We applied them to French newswire articles and produced an annotated corpus. We present observations about the designations used in our manually annotated corpus and the behavior of their triggers. We provide statistics concerning word ambiguity and context of use of event nominals, as well as machine learning experiments showing the difficulty of using lexicons for extracting events.

Within the general purpose of information extraction, detection of event descriptions is often an important clue. An important characteristic of event designation in texts, and especially in media, is that it changes over time. Understanding how these designations evolve is important in information retrieval and information extraction. Our first hypothesis is that, when an event first occurs, media relate it in a very descriptive way (using verbal designations) whereas after some time, they use shorter nominal designations instead. Our second hypothesis is that the number of different nominal designations for an event tends to stabilize itself over time. In this article, we present our methodology concerning the study of the evolution of event designations in French documents from the news agency AFP. For this preliminary study, we focused on 7 topics which have been relatively important in France. Verbal and nominal designations of events have been manually annotated in manually selected topic-related passages. This French corpus contains a total of 2064 annotations. We then provide preliminary interesting statistical results and observations concerning these evolutions.

Cet article décrit une étude sur l’annotation automatique des noms d’événements dans les textes en français. Plusieurs lexiques existants sont utilisés, ainsi que des règles syntaxiques d’extraction, et un lexique composé de façon automatique, permettant de fournir une valeur sur le niveau d’ambiguïté du mot en tant qu’événement. Cette nouvelle information permettrait d’aider à la désambiguïsation des noms d’événements en contexte.

L’extraction des événements désignés par des noms est peu étudiée dans des corpus généralistes. Si des lexiques de noms déclencheurs d’événements existent, les problèmes de polysémie sont nombreux et beaucoup d’événements ne sont pas introduits par des déclencheurs. Nous nous intéressons dans cet article à une hypothèse selon laquelle les verbes induisant la cause ou la conséquence sont de bons indices quant à la présence d’événements nominaux dans leur cotexte.