Cross-lingual Slot Filling from Comparable Corpora
Matthew Snover, Xiang Li, Wen-Pin Lin, Zheng Chen, Suzanne R Tamang, Mingmin Ge, Adam J. Lee, Qi Li, Hao Li, Sam Anzaroot, Heng Ji · 2011
This paper introduces a new task of crosslingual slot filling which aims to discover attributes for entity queries from crosslingual comparable corpora and then present answers in a desired language. It is a very challenging task which suffers from both information extraction and machine translation errors. In this paper we analyze the types of errors produced by five different baseline approaches, and present a novel supervised rescoring based validation approach to incorporate global evidence from very large bilingual comparable corpora. Without using any additional labeled data this new approach obtained 38.5 % relative improvement in Precision and 86.7 % relative improvement in Recall over several state-of-the-art approaches. The ultimate system outperformed monolingual slot filling pipelines built on much larger monolingual corpora. 1