| from __future__ import annotations | |
| from collections import defaultdict | |
| from datasets import DatasetDict, load_dataset | |
| from mteb.abstasks.TaskMetadata import TaskMetadata | |
| from ....abstasks.AbsTaskRetrieval import AbsTaskRetrieval | |
| def load_retrieval_data(dataset_path, eval_splits): | |
| eval_split = eval_splits[0] | |
| corpus_dataset = load_dataset(dataset_path, "corpus") | |
| queries_dataset = load_dataset(dataset_path, "queries") | |
| qrels = load_dataset(dataset_path + "-qrels")[eval_split] | |
| corpus = {e["_id"]: {"text": e["text"]} for e in corpus_dataset["corpus"]} | |
| queries = {e["_id"]: e["text"] for e in queries_dataset["queries"]} | |
| relevant_docs = defaultdict(dict) | |
| for e in qrels: | |
| relevant_docs[e["query-id"]][e["corpus-id"]] = e["score"] | |
| corpus = DatasetDict({eval_split: corpus}) | |
| queries = DatasetDict({eval_split: queries}) | |
| relevant_docs = DatasetDict({eval_split: relevant_docs}) | |
| return corpus, queries, relevant_docs | |
| class GermanQuADRetrieval(AbsTaskRetrieval): | |
| metadata = TaskMetadata( | |
| name="GermanQuAD-Retrieval", | |
| description="Context Retrieval for German Question Answering", | |
| reference="https://www.kaggle.com/datasets/GermanQuAD", | |
| dataset={ | |
| "path": "mteb/germanquad-retrieval", | |
| "revision": "f5c87ae5a2e7a5106606314eef45255f03151bb3", | |
| }, | |
| type="Retrieval", | |
| category="s2p", | |
| eval_splits=["test"], | |
| eval_langs=["deu-Latn"], | |
| main_score="mrr_at_5", | |
| date=None, | |
| form=None, | |
| domains=None, | |
| task_subtypes=None, | |
| license=None, | |
| socioeconomic_status=None, | |
| annotations_creators=None, | |
| dialect=None, | |
| text_creation=None, | |
| bibtex_citation=None, | |
| n_samples=None, | |
| avg_character_length=None, | |
| ) | |
| def load_data(self, **kwargs): | |
| if self.data_loaded: | |
| return | |
| self.corpus, self.queries, self.relevant_docs = load_retrieval_data( | |
| self.metadata_dict["dataset"]["path"], self.metadata_dict["eval_splits"] | |
| ) | |
| self.data_loaded = True | |