Datasets:
Tasks:
Text Retrieval
Sub-tasks:
document-retrieval
Languages:
English
Multilinguality:
monolingual
Size Categories:
10M<n<100M
Create README.md
Browse files
README.md
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# TREC Cast 2019
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[TREC Cast](http://www.treccast.ai) 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.
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## Dataset statistics
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- # Passages: 38,426,252
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- # Topics: 20
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- # Queries: 173
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## Subsets
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### CAR + MSMARCO Collection
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Together CAR and MSMARCO have a size of 6,13G, so downloading will take a while. You can use the collection as followed:
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```python
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collection = load_dataset('trec-cast-2019-multi-turn', 'test_collection')
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```
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The collection has the following data format:
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```
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docno: str
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The document id format is [collection_id_paragraph_id] with collection id and paragraph id separated by an underscore.
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The collection ids are in the set: {MARCO, CAR}. E.g.: CAR_6869dee46ab12f0f7060874f7fc7b1c57d53144a
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text: str
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The content of the passage.
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```
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### Topics
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You can get the topics as followed:
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```python
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topics = load_dataset('trec-cast-2019-multi-turn', 'topics')
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```
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The topics have the following dataformat:
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```
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qid: str
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Query ID of the format "topicId_questionNumber"
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history: str[]
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A list of queries. It can be empty for the first question in a topic.
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query: str
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The query
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```
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### Qrels
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You can get the qrels as followed:
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```python
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qrels = load_dataset('trec-cast-2019-multi-turn', 'qrels')
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```
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The qrels have the following data format:
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```
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qid: str
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Query ID of the format "topicId_questionNumber"
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qrels: List[dict]
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A list of dictionaries with the keys 'docno' and 'relevance'. Relevance is an integer in the range [0, 4]
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```
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