| from __future__ import annotations |
|
|
| import datasets |
|
|
| from mteb.abstasks.TaskMetadata import TaskMetadata |
|
|
| from ....abstasks.AbsTaskRetrieval import AbsTaskRetrieval |
|
|
|
|
| class SyntecRetrieval(AbsTaskRetrieval): |
| _EVAL_SPLITS = ["test"] |
|
|
| metadata = TaskMetadata( |
| name="SyntecRetrieval", |
| description="This dataset has been built from the Syntec Collective bargaining agreement.", |
| reference="https://huggingface.co/datasets/lyon-nlp/mteb-fr-retrieval-syntec-s2p", |
| dataset={ |
| "path": "lyon-nlp/mteb-fr-retrieval-syntec-s2p", |
| "revision": "19661ccdca4dfc2d15122d776b61685f48c68ca9", |
| }, |
| type="Retrieval", |
| category="s2p", |
| eval_splits=_EVAL_SPLITS, |
| eval_langs=["fra-Latn"], |
| main_score="ndcg_at_10", |
| date=None, |
| form=None, |
| domains=None, |
| task_subtypes=None, |
| license=None, |
| socioeconomic_status=None, |
| annotations_creators=None, |
| dialect=[], |
| text_creation=None, |
| bibtex_citation=None, |
| n_samples={"test": 90}, |
| avg_character_length={"test": 62}, |
| ) |
|
|
| def load_data(self, **kwargs): |
| if self.data_loaded: |
| return |
| |
| corpus_raw = datasets.load_dataset( |
| name="documents", |
| **self.metadata_dict["dataset"], |
| ) |
| queries_raw = datasets.load_dataset( |
| name="queries", |
| **self.metadata_dict["dataset"], |
| ) |
|
|
| eval_split = self.metadata_dict["eval_splits"][0] |
| self.queries = { |
| eval_split: { |
| str(i): q["Question"] for i, q in enumerate(queries_raw[eval_split]) |
| } |
| } |
|
|
| corpus_raw = corpus_raw[eval_split] |
| corpus_raw = corpus_raw.rename_column("content", "text") |
| self.corpus = {eval_split: {str(row["id"]): row for row in corpus_raw}} |
|
|
| self.relevant_docs = { |
| eval_split: { |
| str(i): {str(q["Article"]): 1} |
| for i, q in enumerate(queries_raw[eval_split]) |
| } |
| } |
|
|
| self.data_loaded = True |
|
|
