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Learning Recursive Segments for Discourse Parsing

Automatically detecting discourse segments is an important preliminary step towards full discourse parsing. Previous research on discourse segmentation have relied on the assumption that elementary discourse units (EDUs) in a document always form a linear sequence (i.e., they can never be nested). Unfortunately, this assumption turns out to be too strong, for some theories of discourse like SDRT allows for nested discourse units. In this paper, we present a simple approach to discourse segmentation that is able to produce nested EDUs. Our approach builds on standard multi-class classification techniques combined with a simple repairing heuristic that enforces global coherence. Our system was developed and evaluated on the first round of annotations provided by the French Annodis project (an ongoing effort to create a discourse bank for French). Cross-validated on only 47 documents (1,445 EDUs), our system achieves encouraging performance results with an F-score of 73% for finding EDUs.Comment: published at LREC 201

Comparison of different algebras for inducing the temporal structure of texts

International audienceThis paper investigates the impact of using different temporal algebras for learning temporal relations between events. Specifically, we compare three interval-based algebras: Allen \shortcite{Allen83} algebra, Bruce \shortcite{Bruce72} algebra, and the algebra derived from the TempEval-07 campaign. These algebras encode different granularities of relations and have different inferential properties. They in turn behave differently when used to enforce global consistency constraints on the building of a temporal representation. Through various experiments on the TimeBank/AQUAINT corpus, we show that although the TempEval relation set leads to the best classification accuracy performance, it is too vague to be used for enforcing consistency. By contrast, the other two relation sets are similarly harder to learn, but more useful when global consistency is important. Overall, the Bruce algebra is shown to give the best compromise between learnability and expressive power

An empirical study of acknowledgment structures

The subject of our study is one type of "response" in dialogue, usually called acknowledgment or positive feedback. We show here how distinguishing between different acknowledgments is central to the establishment of information. The study is based on a french corpus of direction-giving dialogues which we have gathered. The factors that we investigate about the acknowledgments are their producer, their target and their scope. We focus on the relations between those features and linguistic discourse markers

Predicting globally-coherent temporal structures from texts via endpoint inference and graph decomposition

International audienceAn elegant approach to learning temporal order- ings from texts is to formulate this problem as a constraint optimization problem, which can be then given an exact solution using Integer Linear Programming. This works well for cases where the number of possible relations between temporal entities is restricted to the mere precedence rela- tion [Bramsen et al., 2006; Chambers and Jurafsky, 2008], but becomes impractical when considering all possible interval relations. This paper proposes two innovations, inspired from work on temporal reasoning, that control this combinatorial blow-up, therefore rendering an exact ILP inference viable in the general case. First, we translate our network of constraints from temporal intervals to their end- points, to handle a drastically smaller set of con- straints, while preserving the same temporal infor- mation. Second, we show that additional efficiency is gained by enforcing coherence on particular sub- sets of the entire temporal graphs. We evaluate these innovations through various experiments on TimeBank 1.2, and compare our ILP formulations with various baselines and oracle systems

Excuse me vs. (I’m) sorry as two contrasting markers of interlocutive relations

Dans le cadre de la Théorie de la Relation Interlocutive, nous proposons que l’interprétation sémantique et pragmatique de excuse me et (I’m) sorry, qui ne sont pas, par essence, des marqueurs d’excuse, s’effectue en fonction de deux types de relation interlocutive différents qui conduisent à plusieurs interprétations possibles d’un événement perturbateur. Excuse me est considéré comme marqueur duophonique, c’est-à-dire comme une forme qui impose un désaccord entre un pôle émetteur et un pôle récepteur. On pourra y voir une demande de coopération de l’allocutaire par politesse, pour tenter de réparer un manquement à l’étiquette, ou, bien au contraire, un moyen d’accentuer la nature conflictuelle d’une situation dans un contexte autre qu’un contexte d’excuse. A l’inverse, nous faisons l’hypothèse que (I’m) sorry est une forme monophonique qui s’emploie pour rétablir l’harmonie interlocutive entre les deux pôles. Avec ce marqueur, la coopération de l’allocutaire est considérée comme acquise, ce qui a pour effet de minimiser le conflit dans des situations d’excuse ou autres.Building on the Theory of Interlocutive Relation, we hypothesise that the semantic and pragmatic meaning of excuse me and (I’m) sorry, which are not fundamentally forms of apology, derives from the fact that they establish two different kinds of Interlocutive Relations, guiding towards possible interpretations of a disruptive event. We analyse excuse me as a ‘duophonic marker’, i.e. a form imposing disharmony between an emission and a reception profile. This can be taken as a way to request hearer cooperation for the sake of politeness, in an attempt to remedy a breach of etiquette or, rather to the contrary, as a way to exacerbate the conflicting nature of a situation in non-apologetic contexts. On the other hand, we assume that (I’m) sorry is a ‘monophonic form’ meant to restore interlocutive harmony between the two profiles. Hearer cooperation is then taken for granted and downplays conflict in apologetic and non-apologetic situations