Automatic Identification of Aspectual Classes across Verbal Readings

International audienceThe automatic prediction of aspectual classes is very challenging for verbs whose aspectual value varies across readings, which are the rule rather than the exception. This paper sheds a new perspective on this problem by using a machine learning approach and a rich morpho-syntactic and semantic valency lexicon.In contrast to previous work, where the aspectual value of corpus clauses is determined on the basis of features retrieved from the corpus, we use features extracted from the lexicon, and aim to predict the aspectual value of verbal \textit{readings} rather than verbs.Studying the performance of the classifiers on a set of manually annotated verbal readings, we found that our lexicon provided enough information to reliably predict the aspectual value of verbs across their readings.We additionally tested our predictions for unseen predicates through a task based evaluation, by using them in the automatic detection of temporal relation types in TempEval 2007 tasks for French. These experiments also confirmed the reliability of our aspectual predictions, even for unseen verbs

Formulaic language

The notion of formulaicity has received increasing attention in disciplines and areas as diverse as linguistics, literary studies, art theory and art history. In recent years, linguistic studies of formulaicity have been flourishing and the very notion of formulaicity has been approached from various methodological and theoretical perspectives and with various purposes in mind. The linguistic approach to formulaicity is still in a state of rapid development and the objective of the current volume is to present the current explorations in the field. Papers collected in the volume make numerous suggestions for further development of the field and they are arranged into three complementary parts. The first part, with three chapters, presents new theoretical and methodological insights as well as their practical application in the development of custom-designed software tools for identification and exploration of formulaic language in texts. Two papers in the second part explore formulaic language in the context of language learning. Finally, the third part, with three chapters, showcases descriptive research on formulaic language conducted primarily from the perspectives of corpus linguistics and translation studies. The volume will be of interest to anyone involved in the study of formulaic language either from a theoretical or a practical perspective