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Multi-Multi-View Learning: Multilingual and Multi-Representation Entity Typing
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A Probabilistic Annotation Model for Crowdsourcing Coreference
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Investigating the role of argumentation in the rhetorical analysis of scientific publications with neural multi-task learning models
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Adversarial propagation and zero-shot cross-lingual transfer of word vector specialization
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The EventStatus Corpus
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Abstract:
*Introduction* The EventStatus Corpus was developed by researchers at Texas A&M University, Stanford University and The University of Utah. It consists of approximately 3,000 English and 1,500 Spanish news articles about civil unrest events annotated with temporal tags. This corpus was designed to support the study of the temporal and aspectual properties of major events, that is, whether an event has already happened, is currently happening or may happen in the future. Since it focuses on a single domain (civil unrest events), it may be appropriate for tasks such as event extraction and temporal question answering. *Data* The relevant news articles were sourced from English Gigaword Fifth Edition (LDC2011T07) and Spanish Gigaword Third Edition (LDC2011T12). The civil unrest events include protests, demonstrations, marches and strikes. The data was annotated as PAST, ON-GOING or FUTURE and within each of those categories, as PLANNED, ALERT or POSSIBLE. In addition to the annotated articles, file lists used in experiments for tuning and test are included. 10-fold cross-validations were performed, and the specific 10-fold splits of the test are included as well. All text is presented as plain text and encoded in UTF-8. *Samples* Please view this sample. *Updates* None at this time.
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URL: https://catalog.ldc.upenn.edu/LDC2017T09
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And That's A Fact: Distinguishing Factual and Emotional Argumentation in Online Dialogue ...
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Are you serious?: Rhetorical Questions and Sarcasm in Social Media Dialog ...
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Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue ...
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Domain-specific coreference resolution with lexicalized features
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Conundrums in noun phrase coreference resolution: making sense of the state-of-the-art
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Toward completeness in concept extraction and classification
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Corpus-based semantic lexicon induction with web-based corroboration
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Unified model of phrasal and sentential evidence for information extraction
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Semantic class learning from the web with hyponym pattern linkage graphs
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