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 2023 hosts evaluations in three tracks:

1. Plain Language Adaptation of Biomedical Abstracts (PLABA)
   The goal of the PLABA track is to adapt biomedical abstracts for the general public using plain language.


2. 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.


3. Claim Relation Understanding and Extraction (CRUX)
   The goal of the CRUX track is to develop and evaluate technologies that extract structured information from a variety of unstructured multilingual multimodal sources in order to extract explicit alternative claims about situations and events in noisy, conflicting, and potentially deceptive information environments.