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README.md

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+---
+languages:
+- en-US
+multilinguality:
+- monolingual
+size_categories:
+- 10M<n<100M
+task_categories:
+- text-retrieval
+task_ids:
+- document-retrieval
+---
+
+# TREC Cast 2019 
+
+[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.
+
+## Dataset statistics
+
+- # Passages: 38,426,252
+- # Topics: 20
+- # Queries: 173
+
+## 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:
+```python
+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.
+```
+
+### Topics
+You can get the topics as followed:
+```python
+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:
+```python
+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]
+```