Name
Abstract | ||
|---|---|---|
Natural language parser is usually faced ungrammatical input, such as mistyping or error POS tags. If the parser uses language dependant explicit linguistic knowledge to detect and correct grammatical errors, it is useful for parser. In this paper, we propose a method that uses the Chinese structural auxiliary knowledge to detect and correct ungrammatical Chinese parsing errors. We focus on three error types: miss segmentation, miss POS tags, and miss typing. Experimental results show that appropriate use of evident Chinese structural auxiliary knowledge indeed helps to correct parsing errors and further to improve Chinese parsing performance. © 2009 by Yun Jin, Qing Li, Yingshun Wu, and Young-Gil Kim. |
Year | DOI | Venue |
|---|---|---|
2009 | null | PACLIC |
Keywords | Field | DocType |
abuse,chinese parsing,chinese structural auxiliary,parsing error | Segmentation,Computer science,Speech recognition,Natural language,Artificial intelligence,Natural language processing,Parsing | Conference |
Volume | Issue | Citations |
2 | null | 0 |
PageRank | References | Authors |
0.34 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yun Jin | 1 | 15 | 3.41 |
| Qing Li | 2 | 452 | 30.64 |
| Yingshun Wu | 3 | 0 | 0.34 |
| Young-Gil Kim | 4 | 26 | 5.90 |