Update README.md

README.md

@@ -33,42 +33,69 @@ against the ESCO v1.1.0 skill taxonomy. Layout follows the
 [BEIR](https://github.com/beir-cellar/beir) convention so it is drop-in for
 MTEB-style retrieval evaluators.
 
+This dataset was created for the RecSys-HR 2026 WorkRB challenge.
+
 ## Configs
 
-| config | rows | columns |
-|---|---:|---|
-| `queries` | 50 | `_id` (query id), `text` (ESCO alt-label / surface term to normalise) |
-| `corpus`  | 13,891 | `_id` (ESCO skill URI), `title` (English preferred label), `text` (English description), `esco_version` |
-| `qrels`   | 694,550 | `query-id`, `corpus-id`, `score` (0-4) |
+| config | split | rows | columns |
+|---|---|---:|---|
+| `queries` | `validation` | 50 | `_id` (query id), `text` (ESCO alt-label / surface term to normalise) |
+| `queries` | `test` | 450 | `_id` (query id), `text` (ESCO alt-label / surface term to normalise) |
+| `corpus`  | `corpus` | 13,891 | `_id` (ESCO skill URI), `title` (English preferred label), `text` (English description), `esco_version` |
+| `qrels`   | `validation` | 694,550 | `query-id`, `corpus-id`, `score` (0-4) |
+| `qrels`   | `test` | 6,250,950 | `query-id`, `corpus-id`, `score` (0-4) |
+
+Higher is more relevant. **The corpus is the COMPLETE ESCO v1.1.0 skill
+list (13,891 skills)** The qrels are the full query x corpus grid:
+every query is scored against all 13,891 skills, with score 0 for any skill
+that was not surfaced as relevant.
+
+### Score scale, `validation` split
 
-### Score scale
+| score | volume | meaning |
+|---:|---:|---|
+| 0 | 665,668 | The skill is totally unrelated to the query. |
+| 1 | 28,438 | The skill's domain is correct. It's a plausible skill in a broader context, but not mentioned in this query. |
+| 2 | 312 | The skill could be recommended, but its granularity makes it not core to the query. |
+| 3 | 58 | The skill is strongly relevant for this query, although it is more implied than explicitly demonstrated. |
+| 4 | 74 | The skill is explicitly demonstrated or requested by the query, and is therefore a clearly correct recommendation. |
 
-| score | meaning |
-|---:|---|
-| | 0 | 665,668 |
-| 1 | 28,438 |
-| 2 | 312 |
-| 3 | 58 |
-| 4 | 74 |
+### Score scale, `test` split
 
-Higher is more relevant. **Every query has one row per ESCO v1.1.0
-skill (13,891 rows per query).** 
+| score | volume | meaning |
+|---:|---:|---|
+| 0 | 5,989,638 | The skill is totally unrelated to the query. |
+| 1 | 257,118 | The skill's domain is correct. It's a plausible skill in a broader context, but not mentioned in this query. |
+| 2 | 2,723 | The skill could be recommended, but its granularity makes it not core to the query. |
+| 3 | 966 | The skill is strongly relevant for this query, although it is more implied than explicitly demonstrated. |
+| 4 | 505 | The skill is explicitly demonstrated or requested by the query, and is therefore a clearly correct recommendation. |
 
-## Test split
+## Usage
 
-A `test` split is now available (450 queries, 450 qrels rows).
+```python
+from datasets import load_dataset
+
+queries = load_dataset("TechWolf/Skill-normalisation-ESCO-graded", "queries", split="test")
+corpus  = load_dataset("TechWolf/Skill-normalisation-ESCO-graded", "corpus",  split="corpus")
+qrels   = load_dataset("TechWolf/Skill-normalisation-ESCO-graded", "qrels",   split="test")
+```
+
+Join on ids: `qrels["query-id"]` matches `queries["_id"]`, and
+`qrels["corpus-id"]` matches `corpus["_id"]` (a full ESCO skill URI).
 
-Unlike the `validation` split, the test split is **not yet fully graded** (0-4). Its relevance labels are **real but binary**: `score = 1` marks a genuinely relevant target (derived from the public non-graded ground truths), and every pair not listed is implicit grade 0. The fine-grained 0-4 graded annotations for the test split are withheld during the ongoing RecSys-HR challenge (see [`WorkRB website`](https://techwolf-ai.github.io/workrb-site/challenges/recsys-hr-2026.html)) and will be released afterwards. S
 
 ## Attribution
 
 This dataset uses the ESCO classification of the European Commission
 (ESCO v1.1.0, <https://esco.ec.europa.eu>), licensed under
-[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). The ESCO content
-has been extracted into a tabular subset (skill URI, English preferred label,
+[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). The ESCO content has
+been extracted into a tabular subset (skill URI, English preferred label,
 English description); no semantic modifications were made. The European
 Commission is not responsible for any use of the data.
 
 Source queries come from
 [`ESCO v1.1.0 skill-normalisation pairs`](https://esco.ec.europa.eu)
 (also CC BY 4.0). The judge labels themselves are released under CC BY 4.0.
+
+## Citation
+To be announced