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Acknowledgments

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This work was supported in part by Department of Homeland Security Grant N0014-07-1-0152. We are grateful to Doug Appelt, Ray Mooney, and Siddharth Patwardhan, who provided extremely helpful comments on an ear-lier draft of this chapter.

Bibliography

Ananiadou, S., C. Friedman, and J. Tsujii (2004). Introduction: Named Entity Recognition in Biomedicine. Journal of Biomedical Informat-ics 37 (6).

Ananiadou, S. and J. McNaught (Eds.) (2006). Text Mining for Biology and Biomedicine. Artech House, Inc.

Aone, C. and S. W. Bennett (1996). Applying machine learning to anaphora resolution. In S. Wermter, E. Riloff, and G. Scheler (Eds.), Connec-tionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing, pp. 302–314. Springer-Verlag, Berlin.

Bagga, A. and B. Baldwin (1998). Entity-based Cross-Document Corefer-encing using the Vector Space Model. In Proceedings of the 17th Inter-national Conference on Computational Linguistics.

Banko, M., M. Cafarella, S. Soderland, M. Broadhead, and O. Etzioni (2007). Open Information Extraction from the Web.

Bean, D. and E. Riloff (2004). Unsupervised Learning of Contextual Role Knowledge for Coreference Resolution. In Proceedings of the Annual Meeting of the North American Chapter of the Association for Compu-tational Linguistics (HLT/NAACL 2004).

Bikel, D. M., R. Schwartz, and R. M. Weischedel (1999). An Algorithm that Learns What’s in a Name. Machine Learning 34.

Brin, S. (1998). Extracting Patterns and Relations from the World Wide Web. In WebDB Workshop at EDBT-98.

Bunescu, R. and R. Mooney (2004, July). Collective Information Extraction with Relational Markov Networks. In Proceeding of the 42nd Annual Meeting of the Association for Computational Linguistics, Barcelona, Spain, pp. 438–445.

Bunescu, R. and R. Mooney (2007). Learning to Extract Relations from the Web using Minimal Supervision. In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics.

Califf, M. and R. Mooney (1999). Relational Learning of Pattern-matching Rules for Information Extraction. In Proceedings of the 16th National Conference on Artificial Intelligence.

Califf, M. and R. Mooney (2003). Bottom-up Relational Learning of Pattern Matching rules for Information Extraction. Journal of Machine Learning Research 4, 177–210.

Cardie, C. and K. Wagstaff (1999). Noun Phrase Coreference as Clustering.

In Proc. of the Joint Conference on Empirical Methods in NLP and Very Large Corpora.

Chieu, H. and H. Ng (2002). A Maximum Entropy Approach to Information Extraction from Semi-Structured and Free Text. In Proceedings of the 18th National Conference on Artificial Intelligence.

Chieu, H., H. Ng, and Y. Lee (2003). Closing the Gap: Learning-Based Information Extraction Rivaling Knowledge-Engineering Methods. In Proceedings of the 41th Annual Meeting of the Association for Compu-tational Linguistics.

Choi, Y., C. Cardie, E. Riloff, and S. Patwardhan (2005). Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns. In Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, pp. 355–362.

Ciravegna, F. (2001). Adaptive Information Extraction from Text by Rule Induction and Generalisation. In Proceedings of the 17th International Joint Conference on Artificial Intelligence.

Collins, M. and Y. Singer (1999). Unsupervised Models for Named Entity Classification. In Proceedings of the Joint SIGDAT Conference on Em-pirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-99).

Croft, W. A. (1991). Syntactic Categories and Grammatical Relations.

Chicago, Illinois: University of Chicago Press.

Cucerzan, S. and D. Yarowsky (1999). Language Independent Named En-tity Recognition Combining Morphologi cal and Contextual Evidence. In Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-99).

Cunningham, H., D. Maynard, K. Bontcheva, and V. Tablan (2002). GATE:

A framework and graphical development environment for robust nlp tools and applications. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics.

Dagan, I. and A. Itai (1990). Automatic Processing of Large Corpora for the Resolution of Anaphora References. In Proceedings of the Thirteenth International Conference on Computational Linguistics (COLING-90), pp. 330–332.

Etzioni, O., M. Cafarella, A. Popescu, T. Shaked, S. Soderland, D. Weld, and A. Yates (2005). Unsupervised Named-Entity Extraction from the Web: An Experimental Study. Artificial Intelligence 165 (1), 91–134.

Finkel, J., T. Grenager, and C. Manning (2005, June). Incorporating Non-local Information into Information Extraction Systems by Gibbs Sam-pling. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics, Ann Arbor, MI, pp. 363–370.

Finn, A. and N. Kushmerick (2004, September). Multi-level Boundary Clas-sification for Information Extraction. In In Proceedings of the 15th Eu-ropean Conference on Machine Learning, Pisa, Italy, pp. 111–122.

Fleischman, M. and E. Hovy (2002, August). Fine grained classification of named entities. In Proceedings of the COLING conference.

Fleischman, M., E. Hovy, and A. Echihabi (2003). Offline strategies for on-line question answering: Answering questions before they are asked. In Proceedings of the 41th Annual Meeting of the Association for Compu-tational Linguistics.

Freitag, D. (1998a). Multistrategy Learning for Information Extraction.

In Proceedings of the Fifteenth International Conference on Machine Learning. Morgan Kaufmann Publishers.

Freitag, D. (1998b). Toward General-Purpose Learning for Information Ex-traction. In Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics.

Freitag, D. and A. McCallum (2000, August). Information Extraction with HMM Structures Learned by Stochastic Optimization. In Proceedings of the Seventeenth National Conference on Artificial Intelligence, Austin, TX, pp. 584–589.

Friedman, C. (1986). Analyzing Language in Restricted Domains: Sublan-guage Description and Processing, Chapter Automatic Structuring of Sublanguage Information. Lawrence Erlbaum Associates.

Gooi, C. and J. Allan (2004). Cross-Document Coreference on a Large Scale Corpus. In Proceedings of the Annual Meeting of the North American Chapter of the Association for Computational Linguistics (HLT/NAACL 2004).

Grishman, R., S. Huttunen, and R. Yangarber (2002). Real-Time Event Extraction for Infectious Disease Outbreaks. In Proceedings of HLT 2002 (Human Language Technology Conference).

Gu, Z. and N. Cercone (2006, July). Segment-Based Hidden Markov Mod-els for Information Extraction. In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Sydney, Australia, pp.

481–488.

Haghighi, A. and D. Klein (2007). Unsupervised Coreference Resolution in a Nonparametric Bayesian Model. In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics.

Harabagiu, S., R. Bunescu, and S. Maiorana (2001). Text and Knowledge Mining for Coreference Resolution. In Proceedings of the The Second Meeting of the North American Chapter of the Association for Compu-tational Linguistics.

Hirschman, L., A. Yeh, C. Blaschke, and A. Valencia (2005, May). Overview of BioCreAtIvE: critical assessment of information extraction for biol-ogy. BMC Bioinformatics 6(Suppl 1).

Hobbs, J. R., D. E. Appelt, J. Bear, D. Israel, M. Kameyama, M. Stickel, and M. Tyson (1997). FASTUS: A Cascaded Finite-State Transducer for Extracting Information from Natural-Language Text. In E. Roche and Y. Schabes (Ed.), Finite State Devices for Natural Language Processing, pp. 383–406. MIT Press.

Hobbs, J. R., D. E. Appelt, J. Bear, D. Israel, and M. Tyson (1992).

FASTUS: A System for Extracting Information from Natural-Language Text. SRI Technical Note 519, SRI International, Menlo Park, Califor-nia.

Huffman, S. (1996). Learning Information Extraction Patterns from Ex-amples. In S. Wermter, E. Riloff, and G. Scheler (Eds.), Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing, pp. 246–260. Springer-Verlag, Berlin.

Igo, S. and E. Riloff (2008). Learning to Identify Reduced Passive Verb Phrases with a Shallow Parser. In Proceedings of the 23rd National Con-ference on Artificial Intelligence.

Joshi, A. K. (1996). A Parser from Antiquity: An Early Application of Finite State Transducers to Natural Language Parsing. In European Conference on Artificial Intelligence 96 Workshop on Extended Finite State Models of Language, pp. 33–34.

Kehler, A. (1997). Probabilistic Coreference in Information Extraction. In Proceedings of the Second Conference on Empirical Methods in Natural Language Processing.

Kim, J. and D. Moldovan (1993). Acquisition of Semantic Patterns for Infor-mation Extraction from Corpora. In Proceedings of the Ninth IEEE Con-ference on Artificial Intelligence for Applications, Los Alamitos, CA, pp.

171–176. IEEE Computer Society Press.

Lehnert, W., C. Cardie, D. Fisher, J. McCarthy, E. Riloff, and S. Soderland (1992). University of Massachusetts: Description of the CIRCUS System as Used for MUC-4. In Proceedings of the Fourth Message Understanding Conference (MUC-4), San Mateo, CA, pp. 282–288. Morgan Kaufmann.

Lehnert, W., C. Cardie, D. Fisher, E. Riloff, and R. Williams (1991). Uni-versity of Massachusetts: Description of the CIRCUS System as Used for MUC-3. In Proceedings of the Third Message Understanding Con-ference (MUC-3), San Mateo, CA, pp. 223–233. Morgan Kaufmann.

Lewis, D. D. and J. Catlett (1994). Heterogeneous uncertainty sampling for supervised learning. In Proceedings of the Eleventh International Conference on Machine Learning.

Li, Y., K. Bontcheva, and H. Cunningham (2005, June). Using Uneven Margins SVM and Perceptron for Information Extraction. In Proceed-ings of Ninth Conference on Computational Natural Language Learning, Ann Arbor, MI, pp. 72–79.

Liere, R. and P. Tadepalli (1997). Active learning with committees for text categorization. In Proceedings of the Fourteenth National Conference on Artificial Intelligence.

Light, M., G. Mann, E. Riloff, and E. Breck (2001). Analyses for Elucidating Current Question Answering Technology. Journal for Natural Language Engineering 7 (4).

Mann, G. and D. Yarowsky (2003). Unsupervised Personal Name Disam-biguation. In Proceedings of the Seventh Conference on Natural Lan-guage Learning (CoNLL-2003).

Maslennikov, M. and T. Chua (2007). A Multi-Resolution Framework for Information Extraction from Free Text. In Proceedings of the 45th An-nual Meeting of the Association for Computational Linguistics.

Mayfield, J., D. Alexander, B. Dorr, J. Eisner, T. Elsayed, T. Finin, C. Fink, M. Freedman, N. Garera, P. McNamee, S. Mohammad, D. Oard, C. Pi-atko, A. Sayeed, Z. Syed, R. Weischedel, T. Xu, and D. Yarowsky (2009).

Cross-Document Coreference Resolution: A Key Technology for Learn-ing by ReadLearn-ing. In WorkLearn-ing Notes of the AAAI 2009 SprLearn-ing Symposium on Learning by Reading and Learning to Read.

McCallum, A. and B. Wellner (2004). Conditional Models of Identity Un-certainty with Application to Noun Coreference. In 18th Annual Con-ference on Neural Information Processing Systems.

McCallum, A. K. and K. Nigam (1998). Employing EM and pool-based active learning for text classification. In Proceedings of the Fifteenth International Conference on Machine Learning.

McCarthy, J. and W. Lehnert (1995). Using Decision Trees for Coreference Resolution. In Proc. of the Fourteenth International Joint Conference on Artificial Intelligence.

MUC-4 Proceedings (1992). Proceedings of the Fourth Message Understand-ing Conference (MUC-4). Morgan Kaufmann.

MUC-5 Proceedings (1993). Proceedings of the Fifth Message Understand-ing Conference (MUC-5). San Francisco, CA.

MUC-6 Proceedings (1995). Proceedings of the Sixth Message Understand-ing Conference (MUC-6).

MUC-7 Proceedings (1998). Proceedings of the Seventh Message Under-standing Conference (MUC-7).

Ng, V. and C. Cardie (2002). Improving Machine Learning Approaches to Coreference Resolution. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics.

Niu, C., W. Li, and R. K. Srihari (2004). Weakly Supervised Learning for Cross-Document Person Name Disambiguation Supported by Infor-mation Extraction. In Proceedings of the 42th Annual Meeting of the Association for Computational Linguistics.

Pasca, M. (2007). Weakly-supervised Discovery of Named Entities using Web Search Queries. In Proceedings of the 16th ACM Conference on Information and Knowledge Management (CIKM-07), Lisboa, Portugal, pp. 683–690.

Pasca, M., D. Lin, J. Bigham, A. Lifchits, and A. Jain (2006). Names and Similarities on the Web: Fact Extraction in the Fast Lane. In Proceed-ings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguis-tics (COLING/ACL-06), Sydney, Australia.

Patwardhan, S. and E. Riloff (2007). Effective Information Extraction with Semantic Affinity Patterns and Relevant Regions. In Proceedings of 2007

the Conference on Empirical Methods in Natural Language Processing (EMNLP-2007).

Peng, F. and A. McCallum (2004). Accurate Information Extraction from Research Papers using Conditional Random Fields. In Proceedings of the Annual Meeting of the North American Chapter of the Association for Computational Linguistics (HLT/NAACL 2004).

Phillips, W. and E. Riloff (2007). Exploiting Role-Identifying Nouns and Expressions for Information Extraction. In Proceedings of the 2007 In-ternational Conference on Recent Advances in Natural Language Pro-cessing (RANLP-07), pp. 468–473.

Ravichandran, D. and E. Hovy (2002). Learning Surface Text Patterns for a Question Answering System. In Proceedings of the 40th Annual Meeting on Association for Computational Linguistics.

Riloff, E. (1993). Automatically Constructing a Dictionary for Information Extraction Tasks. In Proceedings of the 11th National Conference on Artificial Intelligence.

Riloff, E. (1996a). An Empirical Study of Automated Dictionary Construc-tion for InformaConstruc-tion ExtracConstruc-tion in Three Domains. Artificial Intelli-gence 85, 101–134.

Riloff, E. (1996b). Automatically Generating Extraction Patterns from Un-tagged Text. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, pp. 1044–1049. The AAAI Press/MIT Press.

Riloff, E. and R. Jones (1999). Learning Dictionaries for Information Ex-traction by Multi-Level Bootstrapping. In Proceedings of the Sixteenth National Conference on Artificial Intelligence.

Roth, D. and W. Yih (2001, August). Relational Learning via Proposi-tional Algorithms: An Information Extraction Case Study. In Proceed-ings of the Seventeenth International Joint Conference on Artificial In-telligence, Seattle, WA, pp. 1257–1263.

Sang, E. F. T. K. and F. D. Meulder (2003). Introduction to the conll-2003 shared task: Language-independent named entity recognition. In Proceedings of CoNLL-2003, pp. 142–147.

Sekine, S. (2006). On-demand information extraction. In Proceedings of Joint Conference of the International Committee on Computa-tional Linguistics and the Association for ComputaComputa-tional Linguistics (COLING/ACL-06.

Shinyama, Y. and S. Sekine (2006, June). Preemptive Information Extrac-tion using Unrestricted RelaExtrac-tion Discovery. In Proceedings of the Hu-man Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, New York City, NY, pp. 304–311.

Soderland, S. (1999). Learning Information Extraction Rules for Semi-structured and Free Text. Machine Learning .

Soderland, S., D. Fisher, J. Aseltine, and W. Lehnert (1995). CRYSTAL:

Inducing a conceptual dictionary. In Proc. of the Fourteenth Interna-tional Joint Conference on Artificial Intelligence, pp. 1314–1319.

Soderland, S. and W. Lehnert (1994). Wrap-Up: A trainable discourse mod-ule for information extraction. Journal of Artificial Intelligence Research (JAIR) 2, 131–158.

Soon, W., H. Ng, and D. Lim (2001). A Machine Learning Approach to Coreference of Noun Phrases. Computational Linguistics 27 (4), 521–

541.

Stevenson, M. and M. Greenwood (2005, June). A Semantic Approach to IE Pattern Induction. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics, Ann Arbor, MI, pp. 379–

386.

Strassel, S., M. Przybocki, K. Peterson, Z. Song, and K. Maeda (2008).

Linguistic Resources and Evaluation Techniques for Evaluation of Cross-Document Automatic Content Extraction. In Proceedings of the Sixth International Language Resources and Evaluation Conference (LREC-08).

Subramaniam, L. V., S. Mukherjea, P. Kankar, B. Srivastava, V. S. Batra, P. V. Kamesam, and R. Kothari (2003). Information extraction from biomedical literature: Methodology, evaluation and an application. In CIKM ’03: Proceedings of the Twelfth International Conference on In-formation and Knowledge Management, pp. 410–417.

Sudo, K., S. Sekine, and R. Grishman (2003). An Improved Extraction Pattern Representation Model for Automatic IE Pattern Acquisition.

In Proceedings of the 41st Annual Meeting of the Association for Com-putational Linguistics (ACL-03).

Surdeanu, M., S. Harabagiu, J. Williams, and P. Aarseth (2003). Using predicate-argument structures for information extraction. In Proceed-ings of the 41th Annual Meeting of the Association for Computational Linguistics.

Thelen, M. and E. Riloff (2002). A Bootstrapping Method for Learning Se-mantic Lexicons Using Extraction Pa ttern Contexts. In Proceedings of the 2002 Conference on Empirical Methods in Natural Language Pro-cessing, pp. 214–221.

Thompson, C. A., M. E. Califf, and R. J. Mooney (1999). Active learning for natural language parsing and information extraction. In Proceedings of the Sixteenth International Conference on Machine Learning.

Yakushiji, A., Y. Miyao, T. Ohta, and J. Tateisi, Y. Tsujii (2006). Auto-matic construction of predicate-argument structure patterns for biomed-ical information extraction. In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing.

Yang, X., J. Su, and C. L. Tan (2005). Improving Pronoun Resolution using Statistics-Based Semantic Compatibility Information. In Proceedings of the 43th Annual Meeting of the Association for Computational Linguis-tics.

Yangarber, R. (2003). Counter-training in the discovery of semantic pat-terns. In Proceedings of the 41th Annual Meeting of the Association for Computational Linguistics.

Yangarber, R., R. Grishman, P. Tapanainen, and S. Huttunen (2000). Au-tomatic Acquisition of Domain Knowledge for Information Extraction.

In Proceedings of the Eighteenth International Conference on Computa-tional Linguistics (COLING 2000).

Yu, K., G. Guan, and M. Zhou (2005, June). Resum´e Information Extrac-tion with Cascaded Hybrid Model. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics, Ann Arbor, MI, pp. 499–506.

Zelenko, D., C. Aone, and A. Richardella (2003). Kernel Methods for Re-lation Extraction. Journal of Machine Learning Research 3.

Zhao, S. and R. Grishman (2005). Extracting Relations with Integrated Information Using Kernel Methods. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL-05), Ann Arbor, Michigan.

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