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metadata
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 against the ESCO v1.1.0 skill taxonomy. Layout follows the 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) and will be released afterwards.

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. 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.