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TREC Cast 2019
TREC Cast have released a document collection with topics and qrels of which a subset has been annotated such that it is suitable for multi-turn conversational search.
Dataset statistics
Subsets
CAR + MSMARCO Collection
Together CAR and MSMARCO have a size of 6,13G, so downloading will take a while. You can use the collection as followed:
collection = load_dataset('trec-cast-2019-multi-turn', 'test_collection')
The collection has the following data format:
docno: str
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}. E.g.: CAR_6869dee46ab12f0f7060874f7fc7b1c57d53144a
text: str
The content of the passage.
Sample
Instead of using the entire data set, you can also download a sample set containing only 200,000 items:
collection = load_dataset('trec-cast-2019-multi-turn', 'test_collection_sample')
Topics
You can get the topics as followed:
topics = load_dataset('trec-cast-2019-multi-turn', 'topics')
The topics have the following dataformat:
qid: str
Query ID of the format "topicId_questionNumber"
history: str[]
A list of queries. It can be empty for the first question in a topic.
query: str
The query
Qrels
You can get the qrels as followed:
qrels = load_dataset('trec-cast-2019-multi-turn', 'qrels')
The qrels have the following data format:
qid: str
Query ID of the format "topicId_questionNumber"
qrels: List[dict]
A list of dictionaries with the keys 'docno' and 'relevance'. Relevance is an integer in the range [0, 4]
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