:memo: Update README.md

README.md

@@ -21,6 +21,14 @@ license: cc-by-sa-4.0
   - [Dataset Description](#dataset-description)
     - [Dataset Summary](#dataset-summary)
     - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+      - [base](#base)
+      - [original](#original)
+    - [Data Fields](#data-fields)
+      - [base](#base-1)
+      - [original](#original-1)
+    - [Data Splits](#data-splits)
     - [Annotations](#annotations)
   - [Additional Information](#additional-information)
     - [Licensing Information](#licensing-information)
@@ -41,6 +49,113 @@ The JaNLI (Japanese Adversarial NLI) dataset, inspired by the English HANS datas
 
 The language data in JaNLI is in Japanese (BCP-47 [ja-JP](https://www.rfc-editor.org/info/bcp47)).
 
+
+
+## Dataset Structure
+
+
+### Data Instances
+When loading a specific configuration, users has to append a version dependent suffix:
+
+```python
+import datasets as ds
+
+dataset: ds.DatasetDict = ds.load_dataset("hpprc/janli")
+print(dataset)
+# DatasetDict({
+#     train: Dataset({
+#         features: ['id', 'premise', 'hypothesis', 'label', 'heuristics', 'number_of_NPs', 'semtag'],
+#         num_rows: 13680
+#     })
+#     test: Dataset({
+#         features: ['id', 'premise', 'hypothesis', 'label', 'heuristics', 'number_of_NPs', 'semtag'],
+#         num_rows: 720
+#     })
+# })
+
+dataset: ds.DatasetDict = ds.load_dataset("hpprc/janli", name="original")
+print(dataset)
+# DatasetDict({
+#     train: Dataset({
+#         features: ['id', 'sentence_A_Ja', 'sentence_B_Ja', 'entailment_label_Ja', 'heuristics', 'number_of_NPs', 'semtag'],
+#         num_rows: 13680
+#     })
+#     test: Dataset({
+#         features: ['id', 'sentence_A_Ja', 'sentence_B_Ja', 'entailment_label_Ja', 'heuristics', 'number_of_NPs', 'semtag'],
+#         num_rows: 720
+#     })
+# })
+```
+
+
+#### base
+
+An example of looks as follows:
+
+```json
+{
+  'id': 12,
+  'premise': '若者がフットボール選手を見ている',
+  'hypothesis': 'フットボール選手を若者が見ている',
+  'label': 0,
+  'heuristics': 'overlap-full',
+  'number_of_NPs': 2,
+  'semtag': 'scrambling'
+}
+```
+
+#### original
+
+An example of looks as follows:
+
+```json
+{
+  'id': 12,
+  'sentence_A_Ja': '若者がフットボール選手を見ている',
+  'sentence_B_Ja': 'フットボール選手を若者が見ている',
+  'entailment_label_Ja': 0,
+  'heuristics': 'overlap-full',
+  'number_of_NPs': 2,
+  'semtag': 'scrambling'
+}
+```
+
+### Data Fields
+
+#### base
+
+A version adopting the column names of a typical NLI dataset.
+
+- `id`: The number of the sentence pair.
+- `premise`: The premise (sentence_A_Ja).
+- `hypothesis`: The hypothesis (sentence_B_Ja).
+- `label`: The correct label for this sentence pair (either `entailment` or `non-entailment`); in the setting described in the paper, non-entailment = neutral + contradiction (entailment_label_Ja).
+- `heuristics`: The heuristics (structural pattern) tag. The tags are: subsequence, constituent, full-overlap, order-subset, and mixed-subset.
+- `number_of_NPs`: The number of noun phrase in a sentence.
+- `semtag`: The linguistic phenomena tag.
+
+#### original
+
+The original version retaining the unaltered column names.
+
+- `id`: The number of the sentence pair.
+- `sentence_A_Ja`: The premise.
+- `sentence_B_Ja`: The hypothesis.
+- `entailment_label_Ja`: The correct label for this sentence pair (either `entailment` or `non-entailment`); in the setting described in the paper, non-entailment = neutral + contradiction
+- `heuristics`: The heuristics (structural pattern) tag. The tags are: subsequence, constituent, full-overlap, order-subset, and mixed-subset.
+- `number_of_NPs`: The number of noun phrase in a sentence.
+- `semtag`: The linguistic phenomena tag.
+
+
+### Data Splits
+
+| name     |  train | validation | test |
+| -------- | -----: | ---------: | ---: |
+| base     | 13,680 |            |  720 |
+| original | 13,680 |            |  720 |
+
+
+
 ### Annotations
 
 The annotation process for this Japanese NLI dataset involves tagging each pair (P, H) of a premise and hypothesis with a label for structural pattern and linguistic phenomenon.