Create README.md

README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- expert-generated
+languages:
+- en
+- de
+licenses:
+- mit
+multilinguality:
+- multilingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- multi-label-classification
+- semantic-similarity-classification
+pretty_name: SV-Ident
+paperswithcode_id: sv-ident
+---
+
+# Dataset Card for SV-Ident
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [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)
+
+## Dataset Description
+
+- **Homepage:** https://vadis-project.github.io/sv-ident-sdp2022/
+- **Repository:** https://github.com/vadis-project/sv-ident
+- **Paper:** [Needs More Information]
+- **Leaderboard:** [Needs More Information]
+- **Point of Contact:** svident2022@googlegroups.com
+
+### Dataset Summary
+
+SV-Ident comprises 4,248 sentences from social science publications in English and German. The data is the official data for the Shared Task: “Survey Variable Identification in Social Science Publications” (SV-Ident) 2022. Visit the homepage to find out more details about the shared task.
+
+### Supported Tasks and Leaderboards
+
+The dataset supports:
+
+- **Variable Detection**: identifying whether a sentence contains a variable mention or not.
+
+- **Variable Disambiguation**: identifying which variable from a given vocabulary is mentioned in a sentence.
+
+### Languages
+
+The text in the dataset is in English and German, as written by researchers. The domain of the texts is scientific publications in the social sciences.
+
+## Dataset Structure
+
+### Data Instances
+
+```
+{
+  "sentence": "Our point, however, is that so long as downward (favorable comparisons overwhelm the potential for unfavorable comparisons, system justification should be a likely outcome amongst the disadvantaged.",
+  "is_variable": 1,
+  "variable": ["exploredata-ZA5400_VarV66", "exploredata-ZA5400_VarV53"],
+  "research_data": ["ZA5400"],
+  "doc_id": "73106",
+  "uuid": "b9fbb80f-3492-4b42-b9d5-0254cc33ac10",
+  "lang": "en",
+}
+```
+
+### Data Fields
+
+The following data fields are provided for documents:
+
+`sentence`:       Textual instance, which may contain a variable mention.<br />
+`is_variable`:    Label, whether the textual instance contains a variable mention (1) or not (0). This column can be used for Task 1 (Variable Detection).<br />
+`variable`:       Variables (separated by a comma ";") that are mentioned in the textual instance. This column can be used for Task 2 (Variable Disambiguation).<br />
+`research_data`:  Research data IDs (separated by a ";") that are relevant for each instance (and in general for each "doc_id").<br />
+`doc_id`:         ID of the source document. Each document is written in one language (either English or German).<br />
+`uuid`:           Unique ID of the instance in uuid4 format.<br />
+`lang`:           Language of the sentence.
+
+### Data Splits
+
+| Split               | No of sentences                       |
+| ------------------- | ------------------------------------  |
+| Train               | 4,248                                 |
+
+## Dataset Creation
+
+### Curation Rationale
+
+The dataset was curated by the VADIS project (https://vadis-project.github.io/).
+The documents were annotated by two expert annotators.
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+The original data are available at GESIS (https://www.gesis.org/home) in an unprocessed format.
+
+#### Who are the source language producers?
+
+[Needs More Information]
+
+### Annotations
+
+#### Annotation process
+
+[Needs More Information]
+
+#### Who are the annotators?
+
+The documents were annotated by two expert annotators.
+
+### Personal and Sensitive Information
+
+The dataset does not include personal or sensitive information.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Needs More Information]
+
+### Discussion of Biases
+
+[Needs More Information]
+
+### Other Known Limitations
+
+[Needs More Information]
+
+## Additional Information
+
+### Dataset Curators
+
+VADIS project (https://vadis-project.github.io/)
+
+### Licensing Information
+
+[Needs More Information]
+
+### Citation Information
+
+```
+@misc{github,
+    author={vadis-project},
+    title={SV-Ident},
+    year={2022},
+    url={https://github.com/vadis-project/sv-ident},
+    }
+```
+
+### Contributions
+
+[Needs More Information]