Year: 2010
Type: conference-paper
Abstract: This paper describes the Error-Annotated German Learner Corpus (EAGLE), a corpus of beginning learner German with grammatical error annotation.The corpus contains online workbook and and hand-written essay data from learners in introductory German courses at The Ohio State University.We introduce an error typology developed for beginning learners of German that focuses on linguistic properties of lexical items present in the learner data and that has three main error categories for syntactic errors: selection, agreement, and word order.The corpus uses an error annotation format that extends the multi-layer standoff format proposed by Lüdeling et al. (2005) to include incremental target hypotheses for each error.In this format, each annotated error includes information about the location of tokens affected by the error, the error type, and the proposed target correction.The multi-layer standoff format allows us to annotate ambiguous errors with more than one possible target correction and to annotate the multiple, overlapping errors common in beginning learner productions.
Author: Adriane Boyd
Institution: The Ohio State University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
Funder: Ohio State University
OpenAlex ID: W48489648