@article{
 title = {Grounding spatial named entities for information extraction and question answering},
 type = {article},
 year = {2003},
 identifiers = {[object Object]},
 pages = {31-38},
 volume = {1},
 websites = {http://portal.acm.org/citation.cfm?doid=1119394.1119399},
 publisher = {Association for Computational Linguistics},
 id = {482f4d15-1dfe-39b1-834e-050732904807},
 created = {2011-12-29T19:53:53.000Z},
 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},
 tags = {named entities},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Leidner2003},
 private_publication = {false},
 abstract = {The task of named entity annotation of unseen text has recently been successfully automated with near-human performance. But the full task involves more than annotation, i.e. identifying the scope of each (continuous) text span and its class (such as place name). It also involves grounding the named entity (i.e. establishing its denotation with respect to the world or a model). The latter aspect has so far been neglected. In this paper, we show how geo-spatial named entities can be grounded using geographic coordinates, and how the results can be visualized using off-the-shelf software. We use this to compare a ?textual surrogate? of a newspaper story, with a ?visual surrogate? based on geographic coordinates.},
 bibtype = {article},
 author = {Leidner, Jochen L and Sinclair, Gail and Webber, Bonnie},
 journal = {Proceedings of the HLTNAACL 2003 workshop on Analysis of geographic references}
}

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