We present the COPLE2 corpus, a learner corpus of Portuguese that includes written and spoken texts produced by learners of Portuguese as a second or foreign language. The corpus includes at the moment a total of 182,474 tokens and 978 texts, classified according to the CEFR scales. The original handwritten productions are transcribed in TEI compliant XML format and keep record of all the original information, such as reformulations, insertions and corrections made by the teacher, while the recordings are transcribed and aligned with EXMARaLDA. The TEITOK environment enables different views of the same document (XML, student version, corrected version), a CQP-based search interface, the POS, lemmatization and normalization of the tokens, and will soon be used for error annotation in stand-off format. The corpus has already been a source of data for phonological, lexical and syntactic interlanguage studies and will be used for a data-informed selection of language features for each proficiency level.

We report on an experiment to evaluate the role of statistical association measures and frequency for the identification of MWE. We base our evaluation on a lexicon of 14.000 MWE comprising different types of word combinations: collocations, nominal compounds, light verbs + predicate, idioms, etc. These MWE were manually validated from a list of n-grams extracted from a 50 million word corpus of Portuguese (a subcorpus of the Reference Corpus of Contemporary Portuguese), using several criteria: syntactic fixedness, idiomaticity, frequency and Mutual Information measure, although no threshold was established, either in terms of group frequency or MI. We report on MWE that were selected on the basis of their syntactic and semantics properties while the MI or both the MI and the frequency show low values, which would constitute difficult cases to establish a cutting point. We analyze the MI values of the MWE selected in our gold dataset and, for some specific cases, compare these values with two other statistical measures.

This paper presents the COMBINA-PT project, a study of corpus-extracted Portuguese Multiword (MW) expressions. The objective of this on-going project is to compile a large lexical database of multiword (MW) units of the Portuguese language, automatically extracted from a balanced 50 million word corpus, and manually validated with the help of lexical association measures. MW expressions considered in the database include named entities and lexical associations with different degrees of cohesion, ranging from frozen groups, which undergo little or no variation, to lexical collocations composed of words that tend to occur together and that constitute syntactic dependencies, although with a low degree of fixedness. This new resource has a two-fold objective: (i) to be an important research tool which supports the development of MW expressions typologies and their lexicographic treatment; (ii) to be of major help in developing and evaluating language processing tools able of dealing with MW expressions.

This presentation reports on an on-going project aimed at building a large lexical database of corpus-extracted multiword (MW) expressions for the Portuguese language. MW expressions were automatically extracted from a balanced 50 million word corpus compiled for this project, furthermore these were statistically interpreted using lexical association measures, followed by a manual validation process. The lexical database covers different types of MW expressions, from named entities to lexical associations with different degrees of cohesion, ranging from totally frozen idioms to favoured co-occurring forms, such as collocations. We aim to achieve two main objectives with this resource. Firstly to build on the large set of data of different types of MW expressions, thus revising existing typologies of collocations and integrating them in a larger theory of MW units. Secondly, to use the extensive hand-checked data as training data to evaluate existing statistical lexical association measures.