Publication
Exploring syntactic relation patterns for question answering
Dan Shen; Dietrich Klakow; Geert-Jan Kruijff
In: Proceedings of The Second International Joint Conference on Natural Language Processing. International Joint Conference on Natural Language Processing (IJCNLP), Jeju Island, Korea, Republic of, Springer, 2005.
Abstract
In this paper, we explore the syntactic relation patterns for open-
domain factoid question answering. We propose a pattern extraction method to
extract the various relations between the proper answers and different types of
question words, including target words, head words, subject words and verbs,
from syntactic trees. We further propose a QA-specific tree kernel to partially
match the syntactic relation patterns. It makes the more tolerant matching be-
tween two patterns and helps to solve the data sparseness problem. Lastly, we
incorporate the patterns into a Maximum Entropy Model to rank the answer
candidates. The experiment on TREC questions shows that the syntactic rela-
tion patterns help to improve the performance by 6.91 MRR based on the com-
mon features.