@inProceedings{
 title = {Subtree Mining for Relation Extraction from Wikipedia},
 type = {inProceedings},
 year = {2007},
 pages = {125-128},
 issue = {April},
 websites = {http://www.aclweb.org/anthology/N/N07/N07-2032},
 id = {f36d2169-ae05-37d9-9964-1f8ba1adf1d3},
 created = {2011-02-24T21:47:51.000Z},
 file_attached = {false},
 profile_id = {5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6},
 group_id = {066b42c8-f712-3fc3-abb2-225c158d2704},
 last_modified = {2017-03-14T14:36:19.698Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Nguyen2007c},
 private_publication = {false},
 abstract = {In this study, we address the problem of extracting relations between entities from Wikipedia's English articles. Our proposed method first anchors the appearance of entities in Wikipedia's articles using neither Named Entity Recognizer (NER) nor coreference resolution tool. It then classifies the relationships between entity pairs using SVM with features extracted from the web structure and subtrees mined from the syntactic structure of text. We evaluate our method on manually annotated data from actual Wikipedia articles.},
 bibtype = {inProceedings},
 author = {Nguyen, Dat P T and Matsuo, Yutaka and Ishizuka, Mitsuru},
 booktitle = {Computational Linguistics}
}

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