Validation Methodology for Expert-Annotated Datasets: Event Annotation Case Study
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Lora Aroyo | Oana Inel | Lora Aroyo | O. Inel
[1] Lora Aroyo,et al. Truth Is a Lie: Crowd Truth and the Seven Myths of Human Annotation , 2015, AI Mag..
[2] Lora Aroyo,et al. Domain-Independent Quality Measures for Crowd Truth Disagreement , 2013, DeRiVE@ISWC.
[3] Angel X. Chang,et al. SUTime: Evaluation in TempEval-3 , 2013, *SEMEVAL.
[4] Estela Saquete Boró,et al. TIPSem (English and Spanish): Evaluating CRFs and Semantic Roles in TempEval-2 , 2010, *SEMEVAL.
[5] Lora Aroyo,et al. Capturing Ambiguity in Crowdsourcing Frame Disambiguation , 2018, HCOMP.
[6] James Pustejovsky,et al. SemEval-2013 Task 1: TempEval-3: Evaluating Time Expressions, Events, and Temporal Relations , 2013, *SEMEVAL.
[7] Miao Fan,et al. Improving Event Detection with Active Learning , 2015, RANLP.
[8] Brendan T. O'Connor,et al. Cheap and Fast – But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks , 2008, EMNLP.
[9] Yejin Choi,et al. Event Detection and Factuality Assessment with Non-Expert Supervision , 2015, EMNLP.
[10] Michael Gertz,et al. HeidelTime: Tuning English and Developing Spanish Resources for TempEval-3 , 2013, *SEMEVAL.
[11] Ralph Grishman,et al. Using Prediction from Sentential Scope to Build a Pseudo Co-Testing Learner for Event Extraction , 2011, IJCNLP.
[12] Lora Aroyo,et al. Studying Topical Relevance with Evidence-based Crowdsourcing , 2018, CIKM.
[13] Tommaso Caselli,et al. Crowdsourcing StoryLines: Harnessing the Crowd for Causal Relation Annotation , 2018, EventStory@Coling.
[14] Sivaji Bandyopadhyay,et al. JU_CSE: A CRF Based Approach to Annotation of Temporal Expression, Event and Temporal Relations , 2013, SemEval@NAACL-HLT.
[15] Tommaso Caselli,et al. Systems' Agreements and Disagreements in Temporal Processing: An Extensive Error Analysis of the TempEval-3 Task , 2018, LREC.
[16] Mihai Surdeanu,et al. The Stanford CoreNLP Natural Language Processing Toolkit , 2014, ACL.
[17] Marie-Francine Moens,et al. KUL: Data-driven Approach to Temporal Parsing of Newswire Articles , 2013, SemEval@NAACL-HLT.
[18] Aldo Gangemi,et al. A Comparison of Knowledge Extraction Tools for the Semantic Web , 2013, ESWC.
[19] Ujwal Gadiraju,et al. JustEvents: A Crowdsourced Corpus for Event Validation with Strict Temporal Constraints , 2017, ECIR.
[20] James Pustejovsky,et al. Temporal and Event Information in Natural Language Text , 2005, Lang. Resour. Evaluation.
[21] Alessandro Lenci,et al. Crowdsourcing for the identification of event nominals: an experiment , 2014, LREC.
[22] Wolfgang Lehner,et al. Enhancing Named Entity Extraction by Effectively Incorporating the Crowd , 2013, BTW Workshops.
[23] Chantal van Son,et al. Resource Interoperability for Sustainable Benchmarking: The Case of Events , 2018, LREC.
[24] Nate Chambers. NavyTime: Event and Time Ordering from Raw Text , 2013, SemEval@NAACL-HLT.
[25] Steven Bethard,et al. ClearTK-TimeML: A minimalist approach to TempEval 2013 , 2013, *SEMEVAL.
[26] Munirathnam Srikanth,et al. LCC-TE: A Hybrid Approach to Temporal Relation Identification in News Text , 2007, Fourth International Workshop on Semantic Evaluations (SemEval-2007).
[27] Lora Aroyo,et al. CrowdTruth 2.0: Quality Metrics for Crowdsourcing with Disagreement (short paper) , 2018, SAD/CrowdBias@HCOMP.
[28] Tommaso Caselli,et al. Temporal Information Annotation: Crowd vs. Experts , 2016, LREC.
[29] Amanda Stent,et al. ATT1: Temporal Annotation Using Big Windows and Rich Syntactic and Semantic Features , 2013, SemEval@NAACL-HLT.
[30] Gianluca Demartini,et al. Hybrid human-machine information systems: Challenges and opportunities , 2015, Comput. Networks.
[31] Lora Aroyo,et al. Harnessing Diversity in Crowds and Machines for Better NER Performance , 2017, ESWC.