Text Analysis Conference

The Text Analysis Conference (TAC) is a series of evaluation workshops organized to encourage research in Natural Language Processing and related applications, by providing a large test collection, common evaluation procedures, and a forum for organizations to share their results. TAC comprises sets of tasks known as "tracks," each of which focuses on a particular subproblem of NLP. TAC tracks focus on end-user tasks, but also include component evaluations situated within the context of end-user tasks.

TAC 2022 hosts evaluations in two tasks:

1. Recognizing Ultra Fine-Grained Entities (RUFES)
   The goal of the KBP RUFES track is to extract and corefer mentions of fine-grained entity types in text.


2. Streaming Multimedia Knowledge Base Population (SM-KBP)
   The goal of the SM-KBP track is to develop and evaluate technologies that extract structured Knowledge Elements (KEs) from a variety of unstructured sources in order to generate explicit alternative interpretations of events, situations, and trends in noisy, conflicting, and potentially deceptive information environments.