Error annotation in a Learner Corpus of Portuguese

Error annotation in a Learner Corpus of Portuguese Iria del Río & Amália Mendes University of Lisbon, Center of Linguistics - CLUL igayo@letras.ulisboa.pt, amaliamendes@letras.ulisboa.pt Abstract We present the error tagging system of the COPLE2 corpus and the first results of its implementation.. The system takes advantage of the corpus architecture and the possibilities of the TEITOK environment to reduce manual effort and produce a final standoff, multi- level annotation with position-based tags that account for the main error types observed in the corpus. The first step of the tagging process involves the manual annotation of errors at the token level. We have already annotated 47% of the corpus using this approach. In a further step, the token-based annotations will be automatically transformed (fully or partially) in position-based error tags. COPLE2 is the first Portuguese learner corpus with error annotation. We expect that this work will support new research in different fields connected with Portuguese as second/foreign language, like Second Language Acquisition/Teaching or Computer Assisted Learning. Keywords: learner corpus, error annotation, second language acquisition. 1. Introduction Error tagging has been proved to be an important aspect in learner corpora research, since it helps to identify problematic areas in the learning process (Granger, 2004) and provides useful data for many areas of study (Díaz- Negrillo and Thompson, 2013). Nevertheless, error tagging is not always present in learner corpora. We can identify at least two important causes for this fact: error- tagging is a high time-consuming task that has to be performed manually; there are no standards, and taxonomies are a result of particular projects with specific interests (Díaz-Negrillo and Fernández-Domíguez, 2006). Error tagging techniques have evolved over the past few years from inline annotations with a unique interpretation, to standoff, multi-layer annotations with multiple error hypotheses. On the contrary, the conceptual design of taxonomies shows less development, with fewer changes in the categories and dimensions observed. Finally, the automatization of the process is still a challenge. We present the error annotation system for the COPLE2 corpus and the first results of its implementation. We show that our system takes advantage of the COPLE2 architecture as well as the TEITOK platform possibilities to reduce manual effort and produce a final annotation that follows the actual trends for error tagging. Since COPLE2 is the first corpus with error annotation for Portuguese, we hope that our work will open new possibilities in the study of Portuguese as second/foreign language. The paper is structured as follows: section 2 shows related work in error annotation; section 3 presents the COPLE2 corpus and its error annotation system; in section 4 we show our first annotation results; finally, section 5 presents the conclusions and future challenges. 2. Related work The analysis of error tagging development leads to three relevant conclusions (among others). First, conceptual aspects related to the design of taxonomies show little variation through the years. Secondly, innovations have affected mainly the technical aspects of the annotation process. Finally, manual annotation is still the most common procedure and …

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