trec-cast-2019 / README.md
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TREC Conversational Assistance Track (CAsT)

There are currently few datasets appropriate for training and evaluating models for Conversational Information Seeking (CIS). The main aim of TREC CAsT is to advance research on conversational search systems. The goal of the track is to create a reusable benchmark for open-domain information centric conversational dialogues.

Year 1 (TREC 2019)

2019 Data

Topics

  • [Training topics] - 30 example training topics
  • [Training judgments] - The judgments are graded on a three point scale (2 very relevant, 1 relevant, and 0 not relevant).
  • [Evaluation topics]- 50 evaluation topics

Sample of Dataset

  • Title: US Judicial history
  • Description: Judicial history in the US including key court cases and what they established.
  • Prompts:
    1. What are the most important US Supreme Court cases?
    2. What did plessy v. ferguson establish?
    3. How about marbury vs madison?
    4. Was it unanimous?
    5. What was the implication of roe vs wade?
    6. What were the main arguments?
    7. What was the point of the brown v board of education?
    8. What were the main arguments?
    9. Why is it important today?

Collection

Document ID format

  • The document id format is [collection_id_paragraph_id] with collection id and paragraph id separated by an underscore.
  • The collection ids are in the set: {MARCO, CAR, WAPO}.
  • The paragraph ids are: standard provided by MARCO and CAR. For WAPO the paragraph ID is [article_id-paragraph_index] where the paragraph_index is the starting from 1-based index of the paragraph using the provided paragraph markup separated by a single dash.
  • Example WaPo combined document id: [WAPO_903cc1eab726b829294d1abdd755d5ab-1], or CAR: [CAR_6869dee46ab12f0f7060874f7fc7b1c57d53144a]

Code and tools

  • TREC-CAsT Tools repository with code and scripts for processing data.
  • The tools contain scripts for parsing the collection into standard indexing formats. It also provides APIs for working with the topics (in text, json, and protocol buffer formats).