TY - GEN
T1 - A preliminary work on classifying time granularities of temporal questions
AU - Li, Wei
AU - Li, Wenjie
AU - Lu, Qin
AU - Wong, Kam Fai
PY - 2005/12/1
Y1 - 2005/12/1
N2 - Temporal question classification assigns time granularities to temporal questions ac-cording to their anticipated answers. It is very important for answer extraction and verification in the literature of temporal question answering. Other than simply distinguishing between "date" and "period", a more fine-grained classification hierarchy scaling down from "millions of years" to "second" is proposed in this paper. Based on it, a SNoW-based classifier, combining user preference, word N-grams, granularity of time expressions, special patterns as well as event types, is built to choose appropriate time granularities for the ambiguous temporal questions, such as When- and How long-like questions. Evaluation on 194 such questions achieves 83.5% accuracy, almost close to manually tagging accuracy 86.2%. Experiments reveal that user preferences make significant contributions to time granularity classification.
AB - Temporal question classification assigns time granularities to temporal questions ac-cording to their anticipated answers. It is very important for answer extraction and verification in the literature of temporal question answering. Other than simply distinguishing between "date" and "period", a more fine-grained classification hierarchy scaling down from "millions of years" to "second" is proposed in this paper. Based on it, a SNoW-based classifier, combining user preference, word N-grams, granularity of time expressions, special patterns as well as event types, is built to choose appropriate time granularities for the ambiguous temporal questions, such as When- and How long-like questions. Evaluation on 194 such questions achieves 83.5% accuracy, almost close to manually tagging accuracy 86.2%. Experiments reveal that user preferences make significant contributions to time granularity classification.
UR - http://www.scopus.com/inward/record.url?scp=33645964921&partnerID=8YFLogxK
M3 - Conference article published in proceeding or book
SN - 3540291725
SN - 9783540291725
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 414
EP - 425
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 2nd International Joint Conference on Natural Language Processing, IJCNLP 2005
Y2 - 11 October 2005 through 13 October 2005
ER -