readme

README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- other
+languages:
+- sv-SE
+licenses:
+- cc-by-4.0
+multilinguality:
+- monolingual
+pretty_name: suc3.1
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- structure-prediction
+task_ids:
+- named-entity-recognition
+- part-of-speech-tagging
+---
+
+# Dataset Card for SUC 3.1
+
+## Dataset Description
+
+- **Homepage:** [https://spraakbanken.gu.se/en/resources/suc3](https://spraakbanken.gu.se/en/resources/suc3)
+- **Repository:** [https://github.com/kb-labb/suc3.1](https://github.com/kb-labb/suc3.1)
+- **Paper:** [SUC 2.0 manual](http://spraakbanken.gu.se/parole/Docs/SUC2.0-manual.pdf)
+- **Point of Contact:** robin.kurtz@kb.se
+
+### Dataset Summary
+
+The dataset is a conversion of the venerable SUC 3.0 dataset into the
+huggingface ecosystem.
+The original dataset does not contain an official train-dev-test split, which is
+introduced here; the tag distribution for the NER tags between the three splits
+is mostly the same.
+
+The dataset has three different types of tagsets: manually annotated POS,
+manually annotated NER, and automatically annotated NER.
+For the automatically annotated NER tags, only sentences were chosen, where the
+automatic and manual annotations would match (with their respective categories).
+
+Additionally we provide remixes of the same data with some or all sentences
+being lowercased.
+
+### Supported Tasks and Leaderboards
+
+- Part-of-Speech tagging
+- Named-Entity-Recognition
+
+### Languages
+
+Swedish
+
+## Dataset Structure
+
+### Data Remixes
+
+- `original_tags` contain the manual NER annotations
+  - `lower` the whole dataset uncased
+  - `lower_mix` some of the dataset uncased
+  - `lower_both` every instance both cased and uncased
+- `simple_tags` contain the automatic NER annotations
+  - `lower` the whole dataset uncased
+  - `lower_mix` some of the dataset uncased
+  - `lower_both` every instance both cased and uncased
+- `simple_tags.no_MSR_TME` contain the automatic NER annotations without `MSR` and `TME` tags
+  - `lower` the whole dataset uncased
+  - `lower_mix` some of the dataset uncased
+  - `lower_both` every instance both cased and uncased
+
+### Data Instances
+
+For each instance, there is an `id`, with an optional `_lower` suffix to mark
+that it has been modified, a `tokens` list of strings containing tokens, a
+`pos_tags` list of strings containing POS-tags, and a `ner_tags` list of strings
+containing NER-tags.
+
+```json
+{"id": "e24d782c-e2475603_lower",
+"tokens": ["-", "dels", "har", "vi", "inget", "index", "att", "g\u00e5", "efter", ",", "vi", "kr\u00e4ver", "allts\u00e5", "ers\u00e4ttning", "i", "40-talets", "penningv\u00e4rde", "."],
+"pos_tags": ["MID", "KN", "VB", "PN", "DT", "NN", "IE", "VB", "PP", "MID", "PN", "VB", "AB", "NN", "PP", "NN", "NN", "MAD"],
+"ner_tags": ["O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O"]}
+```
+
+### Data Fields
+
+- `id`: a string containing the sentence-id
+- `tokens`: a list of strings containing the sentence's tokens
+- `pos_tags`: a list of strings containing the tokens' POS annotations
+- `ner_tags`: a list of strings containing the tokens' NER annotations
+
+### Data Splits
+
+| Dataset Split | Size Percentage of Total Dataset Size | Number of Instances for the Original Tags |
+| ------------- | ------------------------------------- | ----------------------------------------- |
+| train         | 64%                                   | 46\,026                                   |
+| dev           | 16%                                   | 11\,506                                   |
+| test          | 20%                                   | 14\,383                                   |
+
+The `simple_tags` remix has fewer instances due to the requirement to match
+tags.
+
+## Dataset Creation
+
+See the [original webpage](https://spraakbanken.gu.se/en/resources/suc3)
+
+## Additional Information
+
+### Dataset Curators
+
+[Språkbanken](sb-info@svenska.gu.se)
+
+### Licensing Information
+
+CC BY 4.0 (attribution)
+
+### Citation Information
+
+[SUC 2.0 manual](http://spraakbanken.gu.se/parole/Docs/SUC2.0-manual.pdf)