Update dataset card

README.md

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+---
+license: mit
+task_categories:
+- question-answering
+- text-retrieval
+language:
+- en
+tags:
+- search
+- benchmark
+- news
+- twitter
+pretty_name: Desearch Benchmark Questions
+size_categories:
+- 100K<n<1M
+configs:
+- config_name: web
+  data_files:
+  - split: train
+    path: questions/*.jsonl
+- config_name: x
+  data_files:
+  - split: train
+    path: x/*.jsonl
+---
+
+# 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.