Dataset
sec_filings
sec_filings is a small text dataset of 494 rows that pairs natural-language queries about U.S. securities filings with retrieved document facts and ground-truth answers. It is distributed under an unstated license on a public dataset hub.
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Dataset card
What this dataset contains
The dataset is a single CSV containing 494 test rows designed for evaluating retrieval-augmented question answering over SEC filings. Each row links a user-style question to a cited fact drawn from a corporate document and the corresponding numeric or textual answer. Sample tags indicate use cases spanning merger-agreement disclosures and biographical details of issuer executives.
Structure and fields
Four columns are defined: query_id (string identifier for the question), query (the natural-language question), document_ids (a string-encoded reference to the supporting fact from the filing), and answer (the expected response string). The file is provided as CSV and is intended to be loaded with pandas, polars, or the mlcroissant and datasets libraries.
How analysts use it
Practitioners typically use the corpus to benchmark retrieval and reading-comprehension pipelines on real SEC disclosure language rather than synthetic text. The query and document_ids pairings make it suitable for evaluating whether a model can locate a cited fact inside a filing and return the precise answer value. Because the dataset is limited to 494 rows and is distributed under an unstated license, it is best treated as a research or prototyping asset for filing-parsing workflows rather than a production training corpus.
Documentation & references 1
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SEC EDGAR 10-K & 10-Q financial statements for 2,600+ NASDAQ companies.
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