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Past research advocates that, in order to handle the unpredictable nature of multiword expressions (MWEs), their identification should be assisted with lexicons. The choice of the format for such lexicons, however, is far from obvious. We propose the first – to our knowledge – method to quantitatively evaluate some MWE lexicon formalisms based on the notion of observational adequacy. We apply it to derive a simple yet adequate MWE-lexicon formalism, dubbed λ-CSS, based on syntactic dependencies. It proves competitive with lexicons based on sequential representation of MWEs, and even comparable to a state-of-the art MWE identifier.
Diversity can be decomposed into three distinct concepts, namely: variety, balance and disparity. This paper borrows from the extensive formalization and measures of diversity developed in ecology in order to evaluate the variety and balance of multiword expression annotation produced by automatic annotation systems. The measures of richness, normalized richness, and two variations of Hill’s evenness are considered in this paper. We observe how these measures behave against increasingly smaller samples of gold annotations of multiword expressions and use their comportment to validate or invalidate their pertinence for multiword expressions in annotated texts. We apply the validated measures to annotations in 14 languages produced by systems during the PARSEME shared task on automatic identification of multiword expressions and on the gold versions of the corpora. We also explore the limits of such evaluation by studying the impact of lemmatization errors in the Turkish corpus used in the shared task.
The PARSEME (Parsing and Multiword Expressions) project proposes multilingual corpora annotated for multiword expressions (MWEs). In this case study, we focus on the Turkish corpus of PARSEME. Turkish is an agglutinative language and shows high inflection and derivation in word forms. This can cause some issues in terms of automatic morphosyntactic annotation. We provide an overview of the problems observed in the morphosyntactic annotation of the Turkish PARSEME corpus. These issues are mostly observed on the lemmas, which is important for the approximation of a type of an MWE. We propose modifications of the original corpus with some enhancements on the lemmas and parts of speech. The enhancements are then evaluated with an identification system from the PARSEME Shared Task 1.2 to detect MWEs, namely Seen2Seen. Results show increase in the F-measure for MWE identification, emphasizing the necessity of robust morphosyntactic annotation for MWE processing, especially for languages that show high surface variability.
Cet article présente un travail qui consiste à étudier si les scores les plus utilisés pour l’évaluation de la résolution des coréférences constituent des métriques de similarité normalisées. En adoptant une démarche purement expérimentale, nous avons vérifié si les scores MUC, B3 , CEAF, BLANC, LEA et le meta-score CoNLL respectent les bonnes propriétés qui définissent une telle métrique. Notre étude montre que seul le score CEAFm est potentiellement une métrique de similarité normalisée.