Name
Abstract | ||
|---|---|---|
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. |
Year | Venue | Field |
|---|---|---|
2015 | PACLIC | Dependency information,Annotation,Binary classification,Computer science,Dependency structure,Natural language processing,Artificial intelligence,Phrasal verb,Sentence |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Masayuki Komai | 1 | 0 | 0.34 |
| Hiroyuki Shindo | 2 | 75 | 13.80 |
| yuji matsumoto | 3 | 3008 | 300.05 |