init

README.md

@@ -1,7 +1,52 @@
-{"id": "m10",
+---
+language:
+- en
+license:
+- other
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+pretty_name: Relation Mapping
+---
+# Dataset Card for "relbert/relation_mapping"
+## Dataset Description
+- **Repository:** [RelBERT](https://github.com/asahi417/relbert)
+- **Paper:** [https://www.jair.org/index.php/jair/article/view/10583](https://www.jair.org/index.php/jair/article/view/10583)
+- **Dataset:** Relation Mapping
+
+### Dataset Summary
+Relation Mapping is a task to choose optimal combination of word pairs (see more detail in the [paper](https://www.jair.org/index.php/jair/article/view/10583)).
+
+## Dataset Structure
+### Data Instances
+An example looks as follows.
+```
+{
+ "id": "m10",
  "reference": ["seeing", "understanding"],
  "source": ["seeing", "light", "illuminating", "darkness", "view", "hidden"],
  "target": ["understanding", "knowledge", "explaining", "confusion", "interpretation", "secret"],
  "agreement": [68.2, 77.3, 86.4, 86.4, 68.2, 86.4],
-"pos": ["vbg", "nn", "vbg", "nn", "nn", "jj"],
- "target_random": ["knowledge", "interpretation", "explaining", "confusion", "understanding", "secret"]}
+ "pos": ["vbg", "nn", "vbg", "nn", "nn", "jj"],
+ "target_random": ["knowledge", "interpretation", "explaining", "confusion", "understanding", "secret"]
+}
+```
+
+### Data Splits
+|  name   |test|
+|---------|----:|
+|relation_mapping| 33 |
+
+
+### Citation Information
+```
+@article{turney2008latent,
+  title={The latent relation mapping engine: Algorithm and experiments},
+  author={Turney, Peter D},
+  journal={Journal of Artificial Intelligence Research},
+  volume={33},
+  pages={615--655},
+  year={2008}
+}
+```

relation_mapping.py

@@ -42,8 +42,9 @@ class RelationMapping(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         downloaded_file = dl_manager.download_and_extract(_URLS)
-        return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[str(i)]})
-                for i in [datasets.Split.TRAIN, datasets.Split.VALIDATION]]
+        return [datasets.SplitGenerator(
+            name=str(datasets.Split.TRAIN), gen_kwargs={"filepaths": downloaded_file[str(datasets.Split.TRAIN)]})
+        ]
 
     def _generate_examples(self, filepaths):
         _key = 0