Scalable Disambiguation System Capturing Individualities of Mentions
|Title:||Scalable Disambiguation System Capturing Individualities of Mentions||Authors:||Mai, Tiep
Nicholson, Patrick K.
|Permanent link:||http://hdl.handle.net/10197/9892||Date:||27-May-2017||Online since:||2019-04-10T11:33:54Z||Abstract:||Entity disambiguation, or mapping a phrase to its canonical representation in a knowledge base, is a fundamental step in many natural language processing applications. Existing techniques based on global ranking models fail to capture the individual peculiarities of the words and hence, struggle to meet the accuracy-time requirements of many real-world applications. In this paper, we propose a new system that learns specialized features and models for disambiguating each ambiguous phrase in the English language. We train and validate the hundreds of thousands of learning models for this purpose using a Wikipedia hyperlink dataset with more than 170 million labelled annotations. The computationally intensive training required for this approach can be distributed over a cluster. In addition, our approach supports fast queries, efficient updates and its accuracy compares favorably with respect to other state-of-the-art disambiguation systems.||Type of material:||Conference Publication||Publisher:||Springer||Start page:||365||End page:||379||Series/Report no.:||Lecture Notes in Computer Science (volume 10318)||Copyright (published version):||2017 Springer||Keywords:||Entity linking; Entity disambiguation; Wikification; Word-sense disambiguation||DOI:||10.1007/978-3-319-59888-8_31||Language:||en||Status of Item:||Not peer reviewed||Is part of:||Gracia, J., Bond, F., McCrae, F. et al. (eds.). Language, Data, and Knowledge: First International Conference, LDK 2017, Galway, Ireland, June 19-20, 2017, Proceedings||Conference Details:||Language, Data, and Knowledge - First International Conference (LDK 2017), Galway, Ireland, 19-20 June 2017||ISBN:||9783319598871|
|Appears in Collections:||Computer Science Research Collection|
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