dataset: add BarExamQA dataset

mteb/tasks/Retrieval/eng/BarExamQA.py

@@ -0,0 +1,43 @@
+from __future__ import annotations
+
+from mteb.abstasks.TaskMetadata import TaskMetadata
+
+from ....abstasks.AbsTaskRetrieval import AbsTaskRetrieval
+
+
+class BarExamQA(AbsTaskRetrieval):
+    metadata = TaskMetadata(
+        dataset={
+            "path": "isaacus/mteb-barexam-qa",
+            "revision": "49c07b6",
+        },
+        name="BarExamQA",
+        description="A benchmark for retrieving legal provisions that answer US bar exam questions.",
+        reference="https://huggingface.co/datasets/reglab/barexam_qa",
+        type="Retrieval",
+        category="t2t",
+        modalities=["text"],
+        eval_splits=["test"],
+        eval_langs=["eng-Latn"],
+        main_score="ndcg_at_10",
+        date=("2024-08-14", "2025-07-18"),
+        domains=["Legal", "Academic"],
+        task_subtypes=["Question answering"],
+        license="cc-by-sa-4.0",
+        annotations_creators="expert-annotated",
+        dialect=[],
+        sample_creation="found",
+        bibtex_citation="""\
+@inproceedings{Zheng_2025, series={CSLAW ’25},
+   title={A Reasoning-Focused Legal Retrieval Benchmark},
+   url={http://dx.doi.org/10.1145/3709025.3712219},
+   DOI={10.1145/3709025.3712219},
+   booktitle={Proceedings of the Symposium on Computer Science and Law on ZZZ},
+   publisher={ACM},
+   author={Zheng, Lucia and Guha, Neel and Arifov, Javokhir and Zhang, Sarah and Skreta, Michal and Manning, Christopher D. and Henderson, Peter and Ho, Daniel E.},
+   year={2025},
+   month=mar, pages={169–193},
+   collection={CSLAW ’25},
+   eprint={2505.03970}
+}""",
+    )