DEFT Spanish Committed Belief Annotation

Item Name: DEFT Spanish Committed Belief Annotation
Author(s): Jennifer Tracey, Michael Arrigo, Stephanie Strassel
LDC Catalog No.: LDC2019T09
ISBN: 1-58563-892-7
ISLRN: 011-710-836-498-4
DOI: https://doi.org/10.35111/69fx-s086
Release Date: June 17, 2019
Member Year(s): 2019
DCMI Type(s): Text
Data Source(s): discussion forum
Project(s): DEFT
Application(s): anomaly analysis, belief detection
Language(s): Spanish
Language ID(s): spa
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2019T09 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Tracey, Jennifer, Michael Arrigo, and Stephanie Strassel. DEFT Spanish Committed Belief Annotation LDC2019T09. Web Download. Philadelphia: Linguistic Data Consortium, 2019.
Related Works: View

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).

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.

Samples

Please view this source sample and annotation sample.

Updates

None at this time.

Acknowledgement

This material is based on research sponsored by Air Force Research Laboratory and Defense Advance Research Projects Agency under agreement number FA8750-13-2-0045. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Air Force Research Laboratory and Defense Advanced Research Projects Agency or the U.S. Government.

Available Media

View Fees





Login for the applicable fee