Abstract
This paper describes the Nara Institute of Science and Technology's system for the entrance exam pilot task of CLEF 2013 QA4MRE. The core of the system is a similar to the system for the main task of CLEF 2013 QA4MRE. We use minimum error rate training (MERT) to train the weights of the model and also propose a novel method for MERT with the addition of a threshold that defines the certainty with which we must answer questions. The system received a score of 22% c@1.
Original language | English |
---|---|
Title of host publication | 2013 Cross Language Evaluation Forum Conference |
Volume | 1179 |
Publication status | Published - 2013 |
Externally published | Yes |
Event | 2013 Cross Language Evaluation Forum Conference, CLEF 2013 - Valencia, Spain Duration: 23 Sep 2013 → 26 Sep 2013 |
Conference
Conference | 2013 Cross Language Evaluation Forum Conference, CLEF 2013 |
---|---|
Country | Spain |
City | Valencia |
Period | 23/09/13 → 26/09/13 |
Keywords
- Discriminative learning
- Inter-sentence features
- Linear feature model
- Machine reading
- Minimum error rate training
- Question answering