Update README.md

README.md

@@ -1,108 +1 @@
----
-license: other
-language:
-- en
-tags:
-- perplexity
-- evaluation
-- news
-- time-isolated
-configs:
-- config_name: default
-  data_files:
-  - split: "00"
-    path: "data/00.parquet"
-  - split: "01"
-    path: "data/01.parquet"
-  - split: "02"
-    path: "data/02.parquet"
-  - split: "03"
-    path: "data/03.parquet"
-  - split: "04"
-    path: "data/04.parquet"
-  - split: "05"
-    path: "data/05.parquet"
-  - split: "06"
-    path: "data/06.parquet"
-  - split: "07"
-    path: "data/07.parquet"
-  - split: "08"
-    path: "data/08.parquet"
-  - split: "09"
-    path: "data/09.parquet"
-  - split: "10"
-    path: "data/10.parquet"
-  - split: "11"
-    path: "data/11.parquet"
-  - split: "12"
-    path: "data/12.parquet"
-  - split: "13"
-    path: "data/13.parquet"
-  - split: "14"
-    path: "data/14.parquet"
-  - split: "15"
-    path: "data/15.parquet"
-  - split: "16"
-    path: "data/16.parquet"
-  - split: "17"
-    path: "data/17.parquet"
-  - split: "18"
-    path: "data/18.parquet"
-  - split: "19"
-    path: "data/19.parquet"
-  - split: "20"
-    path: "data/20.parquet"
-  - split: "21"
-    path: "data/21.parquet"
-  - split: "22"
-    path: "data/22.parquet"
-  - split: "23"
-    path: "data/23.parquet"
-  - split: "24"
-    path: "data/24.parquet"
-  - split: "25"
-    path: "data/25.parquet"
----
-
-# TheFinAI/ppl — Per-Year News Corpus for Perplexity Evaluation
-
-A held-out news corpus for evaluating per-year perplexity of time-isolated
-language models (TILE / MoE per-year experts).
-
-## Structure
-
-- One split per year, named `00` (= 2000) through `25` (= 2025).
-- Each split contains ~2000 news articles sampled month-stratified
-  (~167/month) from The Guardian Open Platform.
-- Sections kept: world, us-news, uk-news, business, politics, technology,
-  science, environment, society, education, media, law, etc.
-  (Sport, lifestyle, food, fashion, film, books, travel, games dropped.)
-- All articles passed `token_count >= 50` (cl100k_base) filter.
-
-## Schema
-
-| column        | dtype  | note                                  |
-|---------------|--------|---------------------------------------|
-| `source`      | str    | constant `"guardian"`                 |
-| `date`        | int32  | year, e.g. `2003`                     |
-| `pub_date`    | str    | publication date `YYYY-MM-DD`         |
-| `section`     | str    | guardian sectionId                    |
-| `headline`    | str    | webTitle                              |
-| `url`         | str    | webUrl                                |
-| `text`        | str    | full article body (`bodyText`)        |
-| `token_count` | int32  | tiktoken `cl100k_base` token count    |
-
-## Usage
-
-```python
-from datasets import load_dataset
-ds = load_dataset("TheFinAI/ppl", split="03")  # year 2003
-```
-
-## Notes
-
-- Cross-year fairness: all years drawn from the same source pipeline, same
-  section filter, same length filter, same tokenizer. PPL comparisons
-  across years should not be biased by corpus shift.
-- Single-source: only Guardian. For multi-outlet eval, supplement with NYT
-  metadata (`TheFinAI/ppl_nyt` if/when added).
+.