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|a AZU
|b spa
|c AZU
|d OCLCO
|d CGU
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|a 1585638927
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|a 9781585638925
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|a (OCoLC)1305400667
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|a PC4074.5
|b .D344 2019
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|a DEFT Spanish Committed Belief Annotation;
|c Linguistic Data Consortium .
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|a [Philadelphia, Pa.] :
|b Linguistic Data Consortium,
|c 2019
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|a 1 CD-ROM ;
|c 4 3/4 in.
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|a Title from disc label.
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|a "LDC2019T09."
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|a Language(s) Spanish
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|a Release Date: June 17, 2019
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|a Author(s): Jennifer Tracey, Michael Arrigo, Neil Kuster, Stephanie Strassel
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|a Introduction: DEFT Spanish Committed Belief Annotation was developed by the Linguistic Data Consortium (LDC) and consists of approximately 67,000 tokens of Spanish discussion forum text annotated for "committed belief," which marks the level of commitment displayed by the author to the truth of the propositions expressed in the text. DARPA's Deep Exploration and Filtering of Text (DEFT) program aimed to address remaining capability gaps in state-of-the-art natural language processing technologies related to inference, causal relationships and anomaly detection. LDC supported the DEFT program by collecting, creating and annotating a variety of data sources. LDC has also released DEFT Chinese Committed Belief Annotation (LDC2019T03).
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|a Data: The source data is Spanish discussion forum web text collected by LDC. Annotations fall into one of four categories: committed belief, non-committed belief, reported belief and not applicable. Further information about the annotation methodology is contained in the documentation accompanying this release. This publication contains 87 files (67,395 tokens). Annotation files are stored in XML format, and source documents are stored in plain text format. Both types of files are encoded in UTF-8.
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|a Spanish language
|x Data processing
|v Databases.
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|a Speech perception
|x Data processing
|v Databases.
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|a Automatic speech recognition
|v Databases.
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7 |
|a Databases.
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|0 (OCoLC)fst01411643
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|a Tracey, Jennifer
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|a Arrigo, Michael
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1 |
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|a Kuster, Neil
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700 |
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|a Strassel, Stephanie
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|a Linguistic Data Consortium.
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|t Library of Congress classification
|a PC4074.5.D344 2019
|p CDRom
|l ASR
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|i 12876792
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|t Library of Congress classification
|a PC4074.5.D344 2019
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|l ASR
|c ASR-JRLASR
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