Paper: Exploiting Parse Structures for Native Language Identification

ACL ID D11-1148
Title Exploiting Parse Structures for Native Language Identification
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011
Authors

Attempts to profile authors according to their characteristics extracted from textual data, in- cluding native language, have drawn attention in recent years, via various machine learn- ing approaches utilising mostly lexical fea- tures. Drawing on the idea of contrastive analysis, which postulates that syntactic er- rors in a text are to some extent influenced by the native language of an author, this paper explores the usefulness of syntactic features for native language identification. We take two types of parse substructure as features— horizontal slices of trees, and the more gen- eralfeatureschemasfromdiscriminativeparse reranking—and show that using this kind of syntactic feature results in an accuracy score in classification of seven native languages of around 80%, an error red...