*Introduction* TAC KBP English Event Nugget Detection and Coreference - Comprehensive Training and Evaluation Data 2014-2015 was developed by the Linguistic Data Consortium (LDC) and contains training and evaluation data produced in support of the TAC KBP English Event Nugget Detection and Coreference tasks in 2014 and 2015. 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 that can match entities mentioned in natural texts with those appearing in a knowledge base and extract novel information about entities from a document collection and add it to a new or existing knowledge base. The goal of the Event Nugget track was to evaluate system performance on the detection and coreference of sets of attributes referencing events in unstructured text. Event Nuggets consist of a mention of the event from the text and labels to indicate event type, subtype, and realis (an indication of whether an event has actually occurred or not). More information about the Event Nugget track and other TAC KBP evaluations can be found on the NIST TAC website. *Data* Source data is English newswire and discussion forum text collected by LDC. This release includes source documents, gold standard event nugget annotations in multiple formats, coreference information for the nuggets, and tokenized source documents. A summary of the data is below: Year Source Docs Nuggets 2014 351 10,719 2015 360 12,976 *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.

Creator(s)

Ann Bies

Stephanie Strassel

Jeremy Getman

Joe Ellis

Song Chen

Distributor(s)

Linguistic Data Consortium

Right Holder(s)

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