Annotating learner data from a cross-linguistic perspective: a study on ESL/DaF learners' interlanguages

Recent research on first language (L1) acquisition pointed out that the lack of direct, unique mappings between lexical conceptual structure, argument structure and syntax implies that there is a logical problem of language acquisition (LA) in the lexical domain (White 2004). This assumption suggests that aspects of grammar that require not only syntactic knowledge, but also the ability to integrate syntactic knowledge and knowledge from other domains of language is hardly to be acquired by second language (L2) learners (Sorace 2005). In particular, features that belong to the interface between syntax and lexicon may be vulnerable to variability and even deviation with respect to the target language (TL) constraints and may lead to frequent misinterpretation and misuse of prepositional phrase attachments and verb complementation by L2 learners. To verify these assumptions from a cross linguistic perspective, we have carried out a study on a sample of L2 data from a group of English as a Foreign Language (ESL) and Deutsch als Fremdsprache (DaF) learners whose native language is Italian. The main aim of the study is to investigate learners’ difficulty to automatically integrate phrase structure and lexicalsemantic information by focusing on argument structure and complementation in their both English and German interlanguages (ILs). The English-German corpus has been automatically parsed by using VISL applications and language analysis tools (http://beta.visl.sdu.dk/) which can provide both syntactic and semantic information on a given constituent structure. The parsed data have been then extracted and queried by using a concordancer in order to: 1. Test the robustness of the L1 parsing system even when it is applied to learner data. 2. Compare the argument structure representation across languages and interlanguages. 3. Find IL features without tagging errors. The overall hypothesis of the study is that using a L1 tagger on a L2 corpus can help validate generalizations on learner language. As a matter of fact, systematic annotation encoding syntactic as well as morphological and semantic information can help support effective querying for specific problematic areas in such interlanguages.