:sparkles: Update documents and improve code

README.md

@@ -12,7 +12,7 @@ multilinguality:
 - translation
 pretty_name: JSICK
 size_categories:
-- 1K<n<10K
+- 10K<n<100K
 source_datasets:
 - extended|sick
 tags:
@@ -207,35 +207,31 @@ A version adopting the column names of a typical NLI dataset.
 
 ### Data Splits
 
-| name            | train | validation | test |
-| --------------- | ----: | ---------: | ---: |
-| base            |  4500 |            | 4927 |
-| original        |  4500 |            | 4927 |
-| stress          |       |            |  900 |
-| stress-original |       |            |  900 |
-
+| name            | train | validation |  test |
+| --------------- | ----: | ---------: | ----: |
+| base            | 4,500 |            | 4,927 |
+| original        | 4,500 |            | 4,927 |
+| stress          |       |            |   900 |
+| stress-original |       |            |   900 |
 
 
 ### 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.
-The structural relationship between premise and hypothesis sentences is classified into five patterns, with each pattern associated with a type of heuristic that can lead to incorrect predictions of the entailment relation.
-Additionally, 11 categories of Japanese linguistic phenomena and constructions are focused on for generating the five patterns of adversarial inferences.
-
-For each linguistic phenomenon, a template for the premise sentence P is fixed, and multiple templates for hypothesis sentences H are created.
-In total, 144 templates for (P, H) pairs are produced.
-Each pair of premise and hypothesis sentences is tagged with an entailment label (entailment or non-entailment), a structural pattern, and a linguistic phenomenon label.
+To annotate the JSICK dataset, they used the crowdsourcing platform "Lancers" to re-annotate entailment labels and similarity scores for JSICK.
+They had six native Japanese speakers as annotators, who were randomly selected from the platform.
+The annotators were asked to fully understand the guidelines and provide the same labels as gold labels for ten test questions.
 
-The JaNLI dataset is generated by instantiating each template 100 times, resulting in a total of 14,400 examples.
-The same number of entailment and non-entailment examples are generated for each phenomenon.
-The structural patterns are annotated with the templates for each linguistic phenomenon, and the ratio of entailment and non-entailment examples is not necessarily 1:1 for each pattern.
-The dataset uses a total of 158 words (nouns and verbs), which occur more than 20 times in the JSICK and JSNLI datasets.
+For entailment labels, they adopted annotations that were agreed upon by a majority vote as gold labels and checked whether the majority judgment vote was semantically valid for each example.
+For similarity scores, they used the average of the annotation results as gold scores.
+The raw annotations with the JSICK dataset are [publicly available](https://github.com/verypluming/JSICK/blob/main/jsick/jsick-all-annotations.tsv).
+The average annotation time was 1 minute per pair, and Krippendorff's alpha for the entailment labels was 0.65.
 
 
 ## Additional Information
 
-- [verypluming/JaNLI](https://github.com/verypluming/JaNLI)
-- [Hitomi Yanaka, Koji Mineshima, Assessing the Generalization Capacity of Pre-trained Language Models through Japanese Adversarial Natural Language Inference, Proceedings of the 2021 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP (BlackboxNLP2021), 2021.](https://aclanthology.org/2021.blackboxnlp-1.26/)
+- [verypluming/JSICK](https://github.com/verypluming/JSICK)
+- [Compositional Evaluation on Japanese Textual Entailment and Similarity](https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00518/113850/Compositional-Evaluation-on-Japanese-Textual)
+- [JSICK: 日本語構成的推論・類似度データセットの構築](https://www.jstage.jst.go.jp/article/pjsai/JSAI2021/0/JSAI2021_4J3GS6f02/_article/-char/ja)
 
 ### Licensing Information
 
@@ -244,15 +240,32 @@ CC BY-SA 4.0
 ### Citation Information
 
 ```bibtex
-@InProceedings{yanaka-EtAl:2021:blackbox,
-  author    = {Yanaka, Hitomi and Mineshima, Koji},
-  title     = {Assessing the Generalization Capacity of Pre-trained Language Models through Japanese Adversarial Natural Language Inference},
-  booktitle = {Proceedings of the 2021 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP (BlackboxNLP2021)},
-  url       = {https://aclanthology.org/2021.blackboxnlp-1.26/},
-  year      = {2021},
+@article{yanaka-mineshima-2022-compositional,
+    title = "Compositional Evaluation on {J}apanese Textual Entailment and Similarity",
+    author = "Yanaka, Hitomi  and
+      Mineshima, Koji",
+    journal = "Transactions of the Association for Computational Linguistics",
+    volume = "10",
+    year = "2022",
+    address = "Cambridge, MA",
+    publisher = "MIT Press",
+    url = "https://aclanthology.org/2022.tacl-1.73",
+    doi = "10.1162/tacl_a_00518",
+    pages = "1266--1284",
+}
+
+@article{谷中 瞳2021,
+  title={JSICK: 日本語構成的推論・類似度データセットの構築},
+  author={谷中 瞳 and 峯島 宏次},
+  journal={人工知能学会全国大会論文集},
+  volume={JSAI2021},
+  number={ },
+  pages={4J3GS6f02-4J3GS6f02},
+  year={2021},
+  doi={10.11517/pjsai.JSAI2021.0_4J3GS6f02}
 }
 ```
 
 ### Contributions
 
-Thanks to [Hitomi Yanaka](https://hitomiyanaka.mystrikingly.com/) and Koji Mineshima for creating this dataset.
+Thanks to [Hitomi Yanaka](https://hitomiyanaka.mystrikingly.com/) and [Koji Mineshima](https://abelard.flet.keio.ac.jp/person/minesima/index-j.html) for creating this dataset.

jsick.py

@@ -51,12 +51,12 @@ class JSICKDataset(ds.GeneratorBasedBuilder):
         ds.BuilderConfig(
             name="stress",
             version=VERSION,
-            description="fuga",
+            description="The dataset to investigate whether models capture word order and case particles in Japanese.",
         ),
         ds.BuilderConfig(
             name="stress-original",
             version=VERSION,
-            description="fuga",
+            description="The original version of JSICK-stress Test set retaining the unaltered column names.",
         ),
     ]