Seminaire: Alpage (23 mars), Roser Sauri, Are You Sure that This Happened? Assessing the Factuality Degree of Events in Text

Thierry Hamon thierry.hamon at UNIV-PARIS13.FR
Sun Mar 18 08:42:44 UTC 2012

Date: Fri, 16 Mar 2012 17:55:20 +0100
From: Marie Candito <marie.candito at>
Message-ID: <CAKCM-9EZiDnsLnZ=OwVNdJ5S+e8V9NzyqBKVk3dwVe-AEU4mHg at>

************** Séminaire Alpage *******************

Séminaire de l'école doctorale de Paris Diderot

Il s'agit du séminaire de recherche en linguistique informatique
organisé par l'équipe Alpage, équipe mixte Inria -- Paris Diderot,
spécialisée en analyse syntaxique automatique et en traitement du

Le prochain séminaire se tiendra vendredi 23 mars de 11h à 12h30 en
salle 3E91 à l'UFRL, 16, rue de Clisson, 75013 Paris (3e étage gauche)

Toute personne intéressée est la bienvenue.

*Roser Saurí*

*Title:* Are You Sure that This Happened?  Assessing the Factuality
Degree of Events in Text


Identifying the veracity, or *factuality*, of event mentions in text is
fundamental for reasoning about eventualities in discourse. Inferences
derived from events judged as not having happened, or as being only
possible, are different from those derived from events evaluated as

Event factuality involves two separate levels of information. On the one
hand, it deals with polarity, which distinguishes between positive and
negative instantiations of events.  On the other, it has to do with
degrees of certainty (e.g., possible, probable), an information level
generally subsumed under the category of epistemic modality, and which
has been widely discussed in linguistics and philosophy.  In languages
like English, these two levels of information are expressed through a
variety of linguistic devices, from modal auxiliaries and polarity
particles to syntactic constructions of different kind, passing through
a number of lexical predicates, such as verbs and nouns conveying
epistemic evaluations (e.g., *believe, know*, *suspicion, idea*).

This talk aims at contributing to a better understanding of how event
factuality is articulated in natural language, with special focus on
English data.  For that purpose, I will present a linguistic-oriented
computational model which has at its core an algorithm articulating the
effect of factuality relations across levels of syntactic embedding.  As
a proof of concept, this model has been implemented in De Facto, a
factuality profiler for eventualities mentioned in text, and tested
against a corpus built specifically for the task, yielding an F-1
measure of 0.70 (macro-averaging) and 0.80 (micro-averaging). These two
measures mutually compensate for an over-emphasis present in the other
(either on the lesser or greater populated categories), and can
therefore be interpreted as the lower and upper bounds of the De Facto's


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