Word Segmentation Refinement by Wikipedia for Textual Entailment

From Wikipedia Quality
Revision as of 11:16, 11 July 2019 by Adalynn (talk | contribs) (Word Segmentation Refinement by Wikipedia for Textual Entailment -- new article)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

Word Segmentation Refinement by Wikipedia for Textual Entailment - scientific work related to Wikipedia quality published in 2014, written by Chuan-Jie Lin and Yu-Cheng Tu.

Overview

Textual entailment in Chinese differs from the way handling English because of the lack of word delimiters and capitalization. Information from word segmentation and Wikipedia often plays an important role in textual entailment recognition. However, the inconsistency of boundaries of word segmentation and matched Wikipedia titles should be resolved first. This paper proposed 4 ways to incorporate Wikipedia title matching and word segmentation, experimented in several feature combinations. The best system redoes word segmentation after matching Wikipedia titles. The best feature combination for BC task uses content words and Wikipedia titles only, which achieves a macro-average F-measure of 67.33% and an accuracy of 68.9%. The best MC RITE system also achieves a macro-average F-measure of 46.11% and an accuracy of 58.34%. They beat all the runs in NTCIR-10 RITE-2 CT tasks.

Retrieved from "https://wikipediaquality.com/index.php?title=Word_Segmentation_Refinement_by_Wikipedia_for_Textual_Entailment&oldid=18794"