--- license: cc-by-4.0 language: en tags: - retrieval - skill-extraction - esco - graded-relevance configs: - config_name: queries data_files: - split: validation path: queries/validation.parquet - split: test path: queries/test.parquet - config_name: corpus data_files: - split: corpus path: corpus/corpus.parquet - config_name: qrels data_files: - split: validation path: qrels/validation.parquet - split: test path: qrels/test.parquet --- # skill-extraction-tech-graded Graded-relevance annotations for sentences from [`TechWolf/skill-extraction-tech`](https://huggingface.co/datasets/TechWolf/skill-extraction-tech) against the ESCO v1.1.0 skill taxonomy. Layout follows the [BEIR](https://github.com/beir-cellar/beir) convention. The validation split carries full graded (0-4) relevance. A test split is also available with real but binary relevance; see the Test split section below. ## Configs | config | rows | columns | |---|---:|---| | `queries` | 75 | `_id` (sentence id), `text` (sentence) | | `corpus` | 13,891 | `_id` (ESCO skill URI), `title` (English preferred label), `text` (English description), `esco_version` | | `qrels` | 1,041,825 | `query-id`, `corpus-id`, `score` (0-4) | ### Score scale | score | volume | meaning | |---:|---:|---| | 0 | 1,018,085 | The skill is totally unrelated to the sentence. | 1 | 22,923 | The skill's domain is correct. It's a plausible skill in a broader context, but not mentioned in this sentence. | 2 | 339 | The skill could be recommended, but it's granularity makes it not core to the query. | 3 | 309 | The skill is strongly relevant for this query, although it is more implied than explicitly demonstrated. | 4 | 169 | The skill is explicitly demonstrated or requested by the query, and is therefor a clearly correct recommendation. ## Test split A `test` split is now available (338 queries, 583 qrels rows). 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. ## Attribution This dataset uses the ESCO classification of the European Commission (ESCO v1.1.0, ), 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, English description); no semantic modifications were made. The European Commission is not responsible for any use of the data.