| Publication Type |
Journal Article |
| School or College |
College of Engineering |
| Department |
Computing, School of |
| Creator |
Riloff, Ellen M. |
| Other Author |
Igo, Sean |
| Title |
Learning to identify reduced passive verb phrases with a shallow parser |
| Date |
2008 |
| Description |
Our research is motivated by the observation that NLP systems frequently mislabel passive voice verb phrases as being in the active voice when there is no auxiliary verb (e.g., "The man arrested had a long record"). These errors directly impact thematic role recognition and NLP applications that depend on it. We present a learned classifier that can accurately identify reduced passive voice constructions in shallow parsing environments. |
| Type |
Text |
| Publisher |
Association for the Advancement of Artificial Intelligence (AAAI) |
| First Page |
1 |
| Last Page |
4 |
| Subject |
Passive voice; Reduced passive verb phrases; Shallow parser; Learned classifier |
| Subject LCSH |
Information retrieval; Natural language processing (Computer science); Parsing (Computer grammar) |
| Language |
eng |
| Bibliographic Citation |
Igo, S., & Riloff, E. M. (2009). Learning to identify reduced passive verb phrases with a shallow parser. Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI-08), 1-4. |
| Rights Management |
(c)AAAI http://www.aaai.org/ |
| Format Medium |
application/pdf |
| Format Extent |
57,291 bytes |
| Identifier |
ir-main,12438 |
| ARK |
ark:/87278/s62f85z8 |
| Setname |
ir_uspace |
| ID |
705966 |
| Reference URL |
https://collections.lib.utah.edu/ark:/87278/s62f85z8 |
