loading.py

from datasets import load_dataset

dataset_name = "ConditionalQA"
passages = load_dataset("kwang2049/dapr", f"{dataset_name}-corpus", split="test")
for passage in passages:
    passage["_id"]  # passage id
    passage["text"]  # passage text
    passage["title"]  # doc title
    passage["doc_id"]
    passage["paragraph_no"]  # the paragraph number within the document
    passage["total_paragraphs"]  # how many paragraphs/passages in total in the document
    passage["is_candidate"]  # is this passage a candidate for retrieval


from datasets import load_dataset

dataset_name = "ConditionalQA"
passages = load_dataset(
    "kwang2049/dapr", f"{dataset_name}-corpus", split="test", streaming=True
)
for passage in passages:
    passage["_id"]  # passage id
    passage["text"]  # passage text
    passage["title"]  # doc title
    passage["doc_id"]
    passage["paragraph_no"]  # the paragraph number within the document
    passage["total_paragraphs"]  # how many paragraphs/passages in total in the document
    passage["is_candidate"]  # is this passage a candidate for retrieval

from datasets import load_dataset

dataset_name = "ConditionalQA"
docs = load_dataset("kwang2049/dapr", f"{dataset_name}-docs", split="test")
for doc in docs:
    doc["doc_id"]
    doc["title"]  # doc title
    doc["passage_ids"]  # list of passage ids in the document
    doc["passages"]  # list of passage/paragraph texts in the document

from datasets import load_dataset

dataset_name = "ConditionalQA"
qrels = load_dataset("kwang2049/dapr", f"{dataset_name}-qrels", split="test")
for qrel in qrels:
    qrel["query_id"]  # query id (the text is available in ConditionalQA-queries)
    qrel["corpus_id"]  # passage id
    qrel["score"]  # gold judgement


from datasets import load_dataset

qrels = load_dataset("kwang2049/dapr", "nq-hard", split="test")
for qrel in qrels:
    qrel["query_id"]  # query id (the text is available in ConditionalQA-queries)
    qrel["corpus_id"]  # passage id
    qrel["score"]  # gold judgement

    # Additional columns:
    qrel["query"]  # query text
    qrel["text"]  # passage text
    qrel["title"]  # doc title
    qrel["doc_id"]
    qrel["categories"]  # list of categories about this query-passage pair
    qrel["url"]  # url to the document in Wikipedia