The TempEval challenge: identifying temporal relations in text

Aït-Mokhtar, S., Chanod, J.-P., & Roux, C. (2002). Robustness beyond shallowness: Increamental deep parsing. Natural Language Engineering, 8, 121–144.

Allen, J. (1983). Maintaining knowledge about temporal intervals. Communications of the ACM, 26(11), 832–843.

Allen, J. (1984). Towards a general theory of action and time. Artificial Intelligence, 23, 123–154.

Baker, C., Fillmore, C., & Lowe, J. (1998). The Berkeley FrameNet Project. In Joint 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computation Linguistics (COLING-ACL’98). pp. 86–90.

Bethard, S., & Martin, J. H. (2007). CU-TMP: Temporal relation classification using syntactic and semantic features. In Proceedings of the fourth international workshop on semantic evaluations (SemEval-2007) (pp. 129–132). Prague, Czech Republic: Association for Computational Linguistics.

Bethard, S., Martin, J. H., & Klingenstein, S. (2007). Timelines from text: Identification of syntactic temporal relations. In ICSC ’07: Proceedings of the international conference on semantic computing (pp. 11–18). Washington, DC, USA: IEEE Computer Society.

Boguraev, B., & Ando, R. K. (2006). Analysis of TimeBank as a resource for TimeML parsing. In Language Resources and Evaluation Conference, LREC 2006. Genoa, Italy.

Boguraev, B., Pustejovsky, J., Ando, R., & Verhagen, M. (2007). TimeBank evolution as a community resource for TimeML parsing. Language Resource and Evaluation, 41(1), 91–115.

Bramsen, P., Deshpande P., Keok Y., & Barzilay, R. (2006). Inducting temporal graphs. In Proceedings of the 2006 conference on empirical methods in natural language processing (EMNLP 2006) (pp. 189–198).

Chambers, N., Wang, S., & Jurafsky, D. (2007). Classifying temporal relations between events. In Proceedings of the 45th annual meeting of the association for computational linguistics companion volume proceedings of the demo and poster sessions (pp. 173–176). Prague, Czech Republic: Association for Computational Linguistics.

Cheng, Y., Asahara, M., & Matsumoto, Y. (2007). NAIST.Japan: Temporal relation identification using dependency parsed tree. In Proceedings of the fourth international workshop on semantic evaluations (SemEval-2007) (pp. 245–248). Prague, Czech Republic: Association for Computational Linguistics.

Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37–46.

Dietterich, T. (1998). Approximate statistical tests for comparing supervised classification learning algorithms. Neural Computation, 10(7), 1895–1923.

Ferro, L., Mani, I., Sundheim, B., & Wilson, G. (2001). TIDES temporal annotation guidelines, version 1.0.2. Technical report, The MITRE Corporation, McLean, Virginia. Report MTR 01W0000041.

Filatova, E., & Hovy, E., (2001). Assigning time-stamps to event-clauses. In Proceedings of the 2001 ACL workshop on temporal and spatial information processing.

Freksa, C. (1992). Temporal reasoning based on semi-intervals. Artificial Intelligence, 54(1), 199–227.

Hagège, C., & Tannier, X. (2007). XRCE-T: XIP Temporal Module for TempEval campaign. In Proceedings of the fourth international workshop on semantic evaluations (SemEval-2007) (pp. 492–495). Prague, Czech Republic: Association for Computational Linguistics.

Hepple, M., Setzer, A., & Gaizauskas, R. (2007). USFD: Preliminary exploration of features and classifiers for the TempEval-2007 task. In Proceedings of the fourth international workshop on semantic evaluations (SemEval-2007) (pp. 438–441). Prague, Czech Republic: Association for Computational Linguistics.

Hovy, E., Marcus M., Palmer M., Ramshaw L., & Weischedel, R. (2006). OntoNotes: The 90% solution. In Proceedings of the human language technology conference of the NAACL, companion volume: Short papers (pp. 57–60). New York City, USA: Association for Computational Linguistics.

Katz, G., & Arosio, F. (2001). The annotation of temporal information in natural language sentences. In Proceedings of ACL-EACL 2001, workshop for temporal and spatial information processing (pp. 104–111). Toulouse, France.

Kim, J.-D., Ohta, T., & Tsujii, J. (2008). Corpus annotation for mining biomedical events from literature. BMC Bioinformatics, 9(10).

Li, W., Wong, K.-F., & Yuan, C. (2005). A model for processing temporal references in Chinese. In The language of time. Oxford, UK: Oxford University Press.

Mani, I., Wellner, B., Verhagen, M., Lee, C. M., & Pustejovsky, J. (2006). Machine learning of temporal relations. In Proceedings of the 44th annual meeting of the association for computational linguistics. Sydney, Australia.

Meyers, A., Reeves, R., Macleod, C., Szekely, R., Zielinkska, V., Young, B., & Grishman, R. (2004). The NomBank Project: An interim report. In Proceedings of HLT-EACL workshop: Frontiers in Corpus annotation.

Miltsakaki, E., Prasad, R., Joshi, A., & Webber, B. (2004). The Penn discourse Treebank. In Proceedings of fourth international conference on language resources and evaluation (LREC 2004).

Min, C., Srikanth, M., & Fowler, A. (2007). LCC-TE: A hybrid approach to temporal relation identification in news text. In Proceedings of the fourth international workshop on semantic evaluations (SemEval-2007) (pp. 219–222). Prague, Czech Republic: Association for Computational Linguistics.

MUC-6. (1995). Proceedings of the sixth message understanding conference (MUC-6). Defense Advanced Research Projects Agency, Morgan Kaufmann.

MUC-7. (1998). Proceedings of the seventh message understanding conference (MUC-7). Defense Advanced Research Projects Agency. Available at http://www.itl.nist.gov/iaui/894.02/related_projects/muc .

Palmer, M., Gildea, D., & Kingsbury, P. (2005). The proposition bank: An annotated corpus of semantic roles. Computational Linguistics, 31(1).

Puşcaşu, G. (2007). WVALI: Temporal relation identification by syntactico-semantic analysis. In Proceedings of the fourth international workshop on semantic evaluations (SemEval-2007) (pp. 484–487). Prague, Czech Republic: Association for Computational Linguistics.

Pustejovsky, J., Castaño, J., Ingria, R., Saurí, R., Gaizauskas, R., Setzer, A., & Katz, G. (2003a). TimeML: Robust specification of event and temporal expressions in text. In Proceedings of the fifth international workshop on computational semantics (IWCS-5). Tilburg.

Pustejovsky, J., Hanks, P., Saurí, R., See, A., Gaizauskas, R., Setzer, A., Radev, D., Sundheim, B., Day, D., Ferro, L., & Lazo, M. (2003b) The TIMEBANK Corpus. In Proceedings of Corpus linguistics 2003 (pp. 647–656). Lancaster.

Pustejovsky, J., Knippen, R., Littman, J., & Saurí, R. (2005). Temporal and event information in natural language text. Language Resources and Evaluation, 39, 123–164.

Schilder, F. (1997). Temporal relations in English and German narrative discourse. Ph.D. thesis. Edinburgh, UK: University of Edinburgh.

Schilder, F., & Habel, C. (2001). From temporal expressions to temporal information: Semantic tagging of news messages. In Proceedings of the ACL-2001 workshop on temporal and spatial information processing (pp. 1–8). Toulouse, France: Association for Computational Linguistics.

Setzer, A., & Gaizauskas, R. (2000). Annotating events and temporal information in newswire texts. In LREC 2000.

Setzer, A., Gaizauskas, R., & Hepple, M. (2006). The role of inference in the temporal annotation and analysis of text. Journal of Language Resources and Evaluation, 39(2–3), 243–265.

Verhagen, M. (2005). Temporal closure in an annotation environment. Language Resources and Evaluation, 39, 211–241.

Verhagen, M., Gaizauskas, R., Schilder, F., Hepple, M., Katz, G., & Pustejovsky, J. (2007). SemEval-2007 Task 15: TempEval temporal relation identification. In Proceedings of the fourth international workshop on semantic evaluations (SemEval-2007) (pp. 75–80). Prague, Czech Republic: Association for Computational Linguistics.

Vilain, M., Kautz, H., & van Beek, P. (1990). Constraint propagation algorithms: A revised report. In D.S. Weld & J. de Kleer (Eds.), Qualitative reasoning about physical systems (pp. 373–381). San Mateo, CA: Morgan Kaufman.

Witten, I., & Frank, E. (2005). Data mining: Practical machine learning tools and techniques (2nd ed.). San Francisco: Morgan Kaufmann.