WordNet: a lexical database for English
Communications of the ACM
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Gimme' the context: context-driven automatic semantic annotation with C-PANKOW
WWW '05 Proceedings of the 14th international conference on World Wide Web
Unsupervised learning of generalized names
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Named entity recognition using an HMM-based chunk tagger
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
A bootstrapping approach to named entity classification using successive learners
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
HLT '91 Proceedings of the workshop on Speech and Natural Language
Exploiting strong syntactic heuristics and co-training to learn semantic lexicons
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
A bootstrapping method for learning semantic lexicons using extraction pattern contexts
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Experiments with geographic knowledge for information extraction
HLT-NAACL-GEOREF '03 Proceedings of the HLT-NAACL 2003 workshop on Analysis of geographic references - Volume 1
Semi-supervised learning of geographical gazetteers from the internet
HLT-NAACL-GEOREF '03 Proceedings of the HLT-NAACL 2003 workshop on Analysis of geographic references - Volume 1
HLT-NAACL-GEOREF '03 Proceedings of the HLT-NAACL 2003 workshop on Analysis of geographic references - Volume 1
Bootstrapping toponym classifiers
HLT-NAACL-GEOREF '03 Proceedings of the HLT-NAACL 2003 workshop on Analysis of geographic references - Volume 1
Adaptive information extraction from text by rule induction and generalisation
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
An alignment-based approach to semi-supervised relation extraction including multiple arguments
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
Towards heterogeneous resources-based ambiguity reduction of sub-typed geographic named entities
GeoS'11 Proceedings of the 4th international conference on GeoSpatial semantics
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Geographic named entities can be classified into many sub-types that are useful for applications such as information extraction and question answering. In this paper, we present a high-performance bootstrapping algorithm with error correction heuristics and location normalization for the task of geographic named entity annotation with seven sub-types. Location normalization additionally resolves ambiguities of entities with same name and sub-types. In the initial stage, we annotate a raw corpus using a large set of seeds which is automatically selected from a gazetteer so that its quality does not depend on a specific training corpus. From the initial annotation, boundary patterns reflecting phrasal context are learned and applied to the corpus again to obtain new annotation which passes through error correction heuristics. As the bootstrapping loop proceeds, the annotated instances are gradually increased and the learned boundary patterns become gradually richer and more accurate. Through experiments, we explore inter/intra-phrasal context which reflects syntactic constraints of a named entity and several heuristic knowledge for correcting annotation errors introduced by incomplete boundary patterns. The experiments show the effect of the strategies on the learning curve. When our bootstrapping approach was applied to a newspaper corpus, it could achieve 89 F1 value. And the method suggested for location normalization could achieve 95% accuracy at instance level.