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1
Learning Prototypical Functions for Physical Artifacts ...
BASE
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2
Multi-Multi-View Learning: Multilingual and Multi-Representation Entity Typing
Yaghoobzadeh, Yadollah; Schütze, Hinrich; Riloff, Ellen. - : Ludwig-Maximilians-Universität München, 2018
BASE
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3
A Probabilistic Annotation Model for Crowdsourcing Coreference
Kruschwitz, Udo; Chamberlain, Jon; Yu, Juntao. - : Association for Computational Linguistics, 2018
BASE
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4
Investigating the role of argumentation in the rhetorical analysis of scientific publications with neural multi-task learning models
Ponzetto, Simone Paolo; Eckert, Kai; Lauscher, Anne. - : Association for Computational Linguistics, 2018
BASE
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5
Adversarial propagation and zero-shot cross-lingual transfer of word vector specialization
Ponti, Edoardo Maria; Vulić, Ivan; Glavaš, Goran. - : Association for Computational Linguistics, 2018
BASE
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6
The EventStatus Corpus
Huang, Ruihong; Jurafsky, Daniel; Riloff, Ellen. - : Linguistic Data Consortium, 2017. : https://www.ldc.upenn.edu, 2017
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.
URL: https://catalog.ldc.upenn.edu/LDC2017T09
BASE
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7
And That's A Fact: Distinguishing Factual and Emotional Argumentation in Online Dialogue ...
BASE
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8
Are you serious?: Rhetorical Questions and Sarcasm in Social Media Dialog ...
BASE
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9
The EventStatus Corpus ...
Huang, Ruihong; Jurafsky, Daniel; Riloff, Ellen. - : Linguistic Data Consortium, 2017
BASE
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10
Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue ...
BASE
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11
Domain-specific coreference resolution with lexicalized features
Gilbert, Nathan; Riloff, Ellen M.. - : Association for Computational Linguistics, 2014
BASE
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12
Information extraction
In: Handbook of natural language processing (Boca Raton, Fla., 2010), p. 511-532
MPI für Psycholinguistik
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13
Reconcile: A Coreference Resolution Research Platform
BASE
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14
Inducing domain-specific semantic class taggers from (almost) nothing
In: Association for Computational Linguistics. Proceedings of the conference. - Stroudsburg, Penn. : ACL 48 (2010) 1, 275-285
BLLDB
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15
Coreference Resolution With Reconcile
In: DTIC (2010)
BASE
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16
Conundrums in noun phrase coreference resolution: making sense of the state-of-the-art
Riloff, Ellen M.; Stoyanov, Veselin; Gilbert, Nathan; Cardie, Claire. - : Association for Computational Linguistics, 2009
BASE
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17
Toward completeness in concept extraction and classification
Riloff, Ellen M.; Hovy, Eduard; Kozareva, Zornitsa. - : Association for Computational Linguistics, 2009
BASE
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18
Corpus-based semantic lexicon induction with web-based corroboration
Igo, Sean P.; Riloff, Ellen M.. - : Association for Computational Linguistics, 2009
BASE
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19
Unified model of phrasal and sentential evidence for information extraction
Riloff, Ellen M.; Patwardhan, Siddharth. - : Association for Computational Linguistics, 2009
BASE
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20
Semantic class learning from the web with hyponym pattern linkage graphs
Riloff, Ellen M.; Kozareva, Zornitsa; Hovy, Eduard. - : Association for Computational Linguistics, 2008
BASE
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