Towards a language-independent solution: Knowledge base completion by searching the Web and deriving language pattern
Publication in refereed journal

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摘要Knowledge bases (KBs) such as Freebase and Yago are rather incomplete, and the situation is more serious in non-English KBs, such as Chinese KBs. In this paper, we present a language-independent framework to tackle the slot-filling task by searching the Web with high-precision queries, and deriving lightweight extraction patterns. The patterns are based on string matching, and since they make no use of complex NLP resources, which may be unavailable in some languages, they are very language-independent.

We use a traditional bootstrapping approach for extraction, but also use a novel approach to suppress the noise associated with distant supervision: in particular, we use a pseudo-testing method to validate the patterns derived from different sentences. Experiments show that our framework achieves very encouraging results.
著者Lidong Bing, Zhiming Zhang, Wai Lam, William W. Cohen
期刊名稱Knowledge-Based Systems
出版年份2017
月份1
日期1
卷號115
出版社Elsevier
頁次80 - 86
國際標準期刊號0950-7051
電子國際標準期刊號1872-7409
語言美式英語

上次更新時間 2021-19-01 於 01:18