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Real-world observations gathered by a distributed workforce running structured micro-surveys: price checks, shelf-availability readings and local market conditions.
Dataset details:- This dataset is the 2nd iteration following bugs in 1st dataset. The initial data suffered with followoing cases:- (i) The failed reference_answers generation(due error totalling 23) primarly because of 2 reasons/exceptions:- (a) There was normal limit(300 in 1st request) and worst case limit(450 in 3rd request) number of tokens for consolidated 4 refernce_answers per chunk and i
Dataset details:- This dataset is basically mapping of final anchor-positive pair data with their refernce answer. The given input data considered because:- (i) it had the had purest anchor-positive pairs with semantically bound anchors with context/positive. (ii) gave us the best result on final embedding fine tuning model. The anchor-context(positive)-reference_answer data has been generated via
On-the-ground audits of retail shelves: store-level inventory and condition snapshots collected by contracted field visitors with geolocation context: a direct check on availability and product presence.
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.