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t_rex_relational_similarity

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asahi417 commited on Jan 30, 2023

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2018ecf

•

1 Parent(s): bd607ef

fix readme

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t_rex_relation_similarity.py +4 -4

t_rex_relation_similarity.py CHANGED Viewed

@@ -7,7 +7,7 @@ import datasets
 logger = datasets.logging.get_logger(__name__)
 _DESCRIPTION = """T-Rex dataset."""
 _NAME = "t_rex_relation_similarity"
-_VERSION = "0.0.0"
 _CITATION = """
 @inproceedings{elsahar2018t,
   title={T-rex: A large scale alignment of natural language with knowledge base triples},
@@ -24,9 +24,9 @@ MAX_PREDICATE_FREQ = [100, 50, 25, 10]
 _TYPES = [f"filter_unified.min_entity_{a}_max_predicate_{b}" for a, b in product(MIN_ENTITY_FREQ, MAX_PREDICATE_FREQ)]
 _URLS = {i: {
-    str(datasets.Split.TRAIN): [f'{_URL}/t_rex.{i}.train.jsonl'],
-    str(datasets.Split.VALIDATION): [f'{_URL}/t_rex.{i}.validation.jsonl'],
-    str(datasets.Split.TEST): [f'{_URL}/t_rex.filter_unified.test.jsonl']
 } for i in _TYPES}

 logger = datasets.logging.get_logger(__name__)
 _DESCRIPTION = """T-Rex dataset."""
 _NAME = "t_rex_relation_similarity"
+_VERSION = "0.0.1"
 _CITATION = """
 @inproceedings{elsahar2018t,
   title={T-rex: A large scale alignment of natural language with knowledge base triples},
 _TYPES = [f"filter_unified.min_entity_{a}_max_predicate_{b}" for a, b in product(MIN_ENTITY_FREQ, MAX_PREDICATE_FREQ)]
 _URLS = {i: {
+    str(datasets.Split.TRAIN): [f'{_URL}/{i}.train.jsonl'],
+    str(datasets.Split.VALIDATION): [f'{_URL}/{i}.validation.jsonl'],
+    str(datasets.Split.TEST): [f'{_URL}/filter_unified.test.jsonl']
 } for i in _TYPES}