An Efficient Annotation for Phrasal Verbs using Dependency Information
雅之 駒井, Hiroyuki Shindo, Yūji Matsumoto · Institutional Repositories DataBase (IRDB) · 2015
In this paper, we present an efficient semiautomatic method for annotating English phrasal verbs on the OntoNotes corpus.Our method first constructs a phrasal verb dictionary based on Wiktionary, then annotates each candidate example on the corpus as an either a phrasal verb usage or a literal one.For efficient annotation, we use the dependency structure of a sentence to filter out highly plausible positive and negative cases, resulting in a drastic reduction of annotation cost.We also show that a naive binary classification achieves better MWE identification performance than rule-based and sequence-labeling methods.