TAC KBP Belief and Sentiment - Comprehensive Training and Evaluation Data 2016-2017

Item Name: TAC KBP Belief and Sentiment - Comprehensive Training and Evaluation Data 2016-2017
Author(s): Jennifer Tracey, Stephanie Strassel, Michael Arrigo
LDC Catalog No.: LDC2023T13
ISLRN: 872-904-667-640-7
DOI: https://doi.org/10.35111/37dk-bb17
Release Date: December 15, 2023
Member Year(s): 2023
DCMI Type(s): Text
Data Source(s): discussion forum, newswire
Project(s): DEFT, TAC
Application(s): belief detection, sentiment detection
Language(s): English, Mandarin Chinese, Spanish
Language ID(s): eng, cmn, spa
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2023T13 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Tracey, Jennifer, Stephanie Strassel, and Michael Arrigo. TAC KBP Belief and Sentiment - Comprehensive Training and Evaluation Data 2016-2017 LDC2023T13. Web Download. Philadelphia: Linguistic Data Consortium, 2023.
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Introduction

TAC KBP Belief and Sentiment - Comprehensive Training and Evaluation Data 2016-2017 (LDC2023T13) was developed by the Linguistic Data Consortium and contains training and evaluation data produced in support of the 2016 and 2017 TAC KBP Belief and Sentiment (BeSt) evaluation tracks.

Text Analysis Conference (TAC) is a series of workshops organized by the National Institute of Standards and Technology (NIST). TAC was developed to encourage research in natural language processing and related applications by providing a large test collection, common evaluation procedures, and a forum for researchers to share their results. Through its various evaluations, the Knowledge Base Population (KBP) track of TAC encouraged the development of systems to match entities mentioned in natural texts with those appearing in a knowledge base, to extract novel information about entities from a document collection, and to add it to a new or existing knowledge base.

The Belief and Sentiment track involved using a gold standard set of labeled entities, relations, and events in order to create a system to automatically label belief and sentiment about each possible target (entity, relation or event), as well as identifying the entity that holds the belief or sentiment. The goal of the BeSt track was to provide information about beliefs and sentiments held by entities toward other entities, as well as toward events and relations. More information about the TAC KBP Belief and Sentiment track and other TAC KBP evaluations can be found on the NIST TAC website.

Data

The data in this release includes all of the source documents, gold standard entity, relation, and event  annotation, and belief and sentiment annotation. The source document collections cover Chinese, English, and Spanish newswire and discussion forums. The corresponding Knowledge Base (KB) for much of the data - a 2008 snapshot of Wikipedia - is contained in TAC KBP Reference Knowledge Base (LDC2014T16).

All text data is encoded as UTF-8.

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.

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