Automated Phraseology Extraction and Cultural Factors: An Experiment

Jean-Pierre Colson

Jean-Pierre Colson Université catholique de Louvain

Keywords: phraseology, automatic extraction, algorithm, culture

Abstract

This paper reports the results of an experiment with the Parseme 1.1. dataset for English. While the Parseme initiative represented a breakthrough in computational phraseology, it also raised a number of theoretical and practical issues. In this experiment, an attempt is made to improve the results obtained for English, by having recourse to external resources, in the form of a large web corpus. At the same time, attention is paid to the subtle interaction between linguistic tradition, culture and the manipulation of linguistic data in a supervised model for the automatic extraction of verbal multiword expressions. The results show that our algorithm, relying on an open track with external linguistic data, scores better in terms of recall, while deep learning systems yield a better precision. At various stages of the supervised model, the experiment shows that cultural factors play a crucial role.

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Author Biography

Jean-Pierre Colson, Université catholique de Louvain

Jean-Pierre Colson is professor and chairman of the Department of Translation and Interpreting at the University of Louvain (Louvain-la-Neuve, Belgium). He is also a member of the Board of the European Association for Phraseology (Europhras) and has published many papers on phraseology, translation studies and computational linguistics. In the last years his works are dedicated to the automatic processing of multi-word units in large electronic corpora.

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