Datasetpublic

desearch/dataset

Desearch Benchmark Questions Fresh, self-contained benchmark questions for evaluating web and X (Twitter) search. Regenerated daily from recent news and tweets. Each question is answerable from public sources within a dated window — there are no answer keys or source URLs in the public data, so systems have to actually search rather than recall. Subsets Path Lane Built from questions/ Web / news Recent news articles (RSS + news sitemaps) x/ X /… See the full description on the dataset page: https://huggingface.co/datasets/desearch/dataset.

sourceHugging Facemitupdated 6h agoView on Hugging Face

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Dataset Card

Desearch Benchmark Questions

Fresh, self-contained benchmark questions for evaluating web and X (Twitter) search. Regenerated daily from recent news and tweets. Each question is answerable from public sources within a dated window — there are no answer keys or source URLs in the public data, so systems have to actually search rather than recall.

Subsets

Path	Lane	Built from
`questions/`	Web / news	Recent news articles (RSS + news sitemaps)
`x/`	X / Twitter	High-signal tweets from the past 24h

Files are one per day: <YYYY-MM-DD>.jsonl (web) and x-<YYYY-MM-DD>.jsonl (X).

Schema

Every row is source-free:

json

{
  "id": "…",
  "question": "…",
  "difficulty": "easy | medium | hard",
  "start_date": "YYYY-MM-DDTHH:MM:SSZ",
  "end_date": "YYYY-MM-DDTHH:MM:SSZ"
}

start_date/end_date bound the window in which the question is answerable — use them as a date filter when searching. Gold answers are kept private and are never uploaded.

Loading

python

from datasets import load_dataset

web = load_dataset("desearch/dataset", "web", split="train")
x = load_dataset("desearch/dataset", "x", split="train")

Updates

Regenerated daily by an open-source generator (news twice daily, X once daily), so the set grows one file per lane per day.