Create README.md

README.md

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+---
+YAML tags:
+annotations_creators:
+- found
+language_creators:
+- found
+- expert-generated
+languages:
+- hu
+licenses:
+- bsd-2-clause
+multilinguality:
+- monolingual
+pretty_name: HuSST
+size_categories:
+- unknown
+source_datasets:
+- extended|other
+task_categories:
+- text_classification
+- text_scoring
+task_ids:
+- sentiment_classification
+- sentiment_scoring
+---
+
+# Dataset Card for HuSST
+
+## Table of Contents
+
+- [Table of Contents](#table-of-contents)
+
+- [Dataset Description](#dataset-description)
+
+  - [Dataset Summary](#dataset-summary)
+
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+
+  - [Languages](#languages)
+
+- [Dataset Structure](#dataset-structure)
+
+  - [Data Instances](#data-instances)
+
+  - [Data Fields](#data-fields)
+
+  - [Data Splits](#data-splits)
+
+- [Dataset Creation](#dataset-creation)
+
+  - [Curation Rationale](#curation-rationale)
+
+  - [Source Data](#source-data)
+
+  - [Annotations](#annotations)
+
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+
+  - [Discussion of Biases](#discussion-of-biases)
+
+  - [Other Known Limitations](#other-known-limitations)
+
+- [Additional Information](#additional-information)
+
+  - [Dataset Curators](#dataset-curators)
+
+  - [Licensing Information](#licensing-information)
+
+  - [Citation Information](#citation-information)
+
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:**
+
+- **Repository:**
+
+[HuCoPA dataset](https://github.com/nytud/HuSST)
+
+- **Paper:**
+
+- **Leaderboard:**
+
+- **Point of Contact:**
+
+[lnnoemi](mailto:[email protected])
+
+### Dataset Summary
+
+This is the dataset card for the Hungarian version of the Stanford Sentiment Treebank. This dataset which is also part of the Hungarian Language Understanding Evaluation Benchmark Kit [HuLU](hulu.nlp.nytud.hu). The corpus was created by translating and re-annotating the original SST (Roemmele et al., 2011).
+
+### Supported Tasks and Leaderboards
+
+'sentiment classification'
+
+
+'sentiment scoring'
+
+### Languages
+
+The BCP-47 code for Hungarian, the only represented language in this dataset, is hu-HU. 
+
+## Dataset Structure
+
+### Data Instances
+
+For each instance, there is an id, a sentence and a sentiment label.
+
+An example:
+
+```
+{
+"Sent_id": "dev_0",
+"Sent": "Nos, a Jason elment Manhattanbe és a Pokolba kapcsán, azt hiszem, az elkerülhetetlen folytatások ötletlistájáról kihúzhatunk egy űrállomást 2455-ben (hé, ne lődd   le a poént).",
+"Label": "neutral"
+    }
+
+```
+
+### Data Fields
+
+- Sent_id: unique id of the instances, an integer between 1 and 1000;
+
+- Sent: the sentence, translation of an instance of the SST dataset;
+
+- Label: "negative", "neutral", or "positive".
+
+### Data Splits
+
+HuSST has 3 splits: *train*, *validation* and *test*. 
+
+| Dataset split | Number of instances in the split |
+
+|---------------|----------------------------------|
+
+| train         | 9344                              |
+
+| validation    | 1168                              |
+
+| test          | 1168                              |
+
+The test data is distributed without the labels. To evaluate your model, please [contact us](mailto:[email protected]), or check [HuLU's website](hulu.nlp.nytud.hu) for an automatic evaluation (this feature is under construction at the moment). 
+
+## Dataset Creation
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+The data is a translation of the content of the SST dataset (only the whole sentences were used). Each sentence was translated by a human translator. Each translation was manually checked and further refined by another annotator. 
+
+### Annotations
+
+#### Annotation process
+
+The translated sentences were annotated by three human annotators with one of the following labels: negative, neutral and positive. Each sentence was then curated by a fourth annotator (the 'curator'). The final label is the decision of the curator based on the three labels of the annotators.
+
+#### Who are the annotators?
+
+The translators were native Hungarian speakers with English proficiency. The annotators were university students with some linguistic background. 
+
+## Additional Information
+
+### Licensing Information
+
+
+### Citation Information
+
+If you use this resource or any part of its documentation, please refer to:
+
+Ligeti-Nagy, N., Ferenczi, G., Héja, E., Jelencsik-Mátyus, K., Laki, L. J., Vadász, N., Yang, Z. Gy. and Vadász, T. (2022) HuLU: magyar nyelvű benchmark adatbázis
+kiépítése a neurális nyelvmodellek kiértékelése céljából [HuLU: Hungarian benchmark dataset to evaluate neural language models]. XVIII. Magyar Számítógépes Nyelvészeti Konferencia. (in press)
+
+```
+
+@inproceedings{ligetinagy2022hulu,
+  title={HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából},
+  author={Ligeti-Nagy, N. and Ferenczi, G. and Héja, E. and Jelencsik-Mátyus, K. and Laki, L. J. and Vadász, N. and Yang, Z. Gy. and Vadász, T.},
+  booktitle={XVIII. Magyar Számítógépes Nyelvészeti Konferencia},
+  year={2022}
+}
+
+```
+
+and to:
+
+Socher et al. (2013), Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank. In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. 1631--1642.
+
+```
+
+@inproceedings{socher-etal-2013-recursive,
+    title = "Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank",
+    author = "Socher, Richard  and
+      Perelygin, Alex  and
+      Wu, Jean  and
+      Chuang, Jason  and
+      Manning, Christopher D.  and
+      Ng, Andrew  and
+      Potts, Christopher",
+    booktitle = "Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing",
+    month = oct,
+    year = "2013",
+    address = "Seattle, Washington, USA",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/D13-1170",
+    pages = "1631--1642",
+}
+
+```
+
+### Contributions
+
+Thanks to [lnnoemi](https://github.com/lnnoemi) for adding this dataset.