Update README.md

README.md

@@ -1,19 +1,44 @@
 ---
-task_categories:
-- text2text-generation
+annotations_creators:
+- no-annotation
 language:
 - de
+language_creators:
+- expert-generated
+license:
+- other
+multilinguality:
+- translation
+- monolingual
 pretty_name: DEplain-web
 size_categories:
-- 1K<n<10K
+- <1K
+source_datasets:
+- original
+tags:
+- web-text
+- plain language
+- easy-to-read language
+- document simplification
+task_categories:
+- text2text-generation
 task_ids:
 - text-simplification
-multilinguality:
-- monolingual
 ---
 
-# Dataset Card for DEplain-web
-In the following, we provide a dataset for DEplain-APA (following Huggingface's data cards). 
+
+# DEplain-web-doc: A corpus for German Document Simplification
+DEplain-web-doc is a subcorpus of DEplain [Stodden et. al., 2023]((https://arxiv.org/abs/2305.18939)) for document simplification. 
+The corpus consists of 396 (199/50/147) parallel documents crawled from the web in standard German and plain German (or easy-to-read German). All documents are either published under an open license or the copyright holders gave us the permission to share the data.
+If you are interested in a larger corpus, please check our paper and the provided web crawler to download more parallel documents with a closed license.
+
+Human annotators also sentence-wise aligned the 147 documents of the test set to build a corpus for sentence simplification. 
+For the sentence-level version of this corpus, please see [https://huggingface.co/datasets/DEplain/DEplain-web-sent](https://huggingface.co/datasets/DEplain/DEplain-web-sent).
+The documents of the training and development set were automatically aligned using MASSalign. 
+You can find this data here: [https://github.com/rstodden/DEPlain/](https://github.com/rstodden/DEPlain/tree/main/E__Sentence-level_Corpus/DEplain-web-sent/auto/open).
+If you use this data, please use with caution as the alignment quality might be error-prone. 
+
+# Dataset Card for DEplain-web-doc
 
 ## Table of Contents
 - [Dataset Description](#dataset-description)
@@ -39,41 +64,41 @@ In the following, we provide a dataset for DEplain-APA (following Huggingface's
   - [Citation Information](#citation-information)
   - [Contributions](#contributions)
 
-### Dataset Description
+## Dataset Description
 
 - **Repository:** [DEplain-web GitHub repository](https://github.com/rstodden/DEPlain)
 - **Paper:**  Regina Stodden, Momen Omar, and Laura Kallmeyer. 2023. ["DEplain: A German Parallel Corpus with Intralingual Translations into Plain Language for Sentence and Document Simplification."](https://arxiv.org/abs/2305.18939). In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Toronto, Canada. Association for Computational Linguistics.
 - **Point of Contact:** [Regina Stodden]([email protected])
 
-#### Dataset Summary
+### Dataset Summary
 
 [DEplain-web](https://github.com/rstodden/DEPlain) [(Stodden et al., 2023)](https://arxiv.org/abs/2305.18939) is a dataset for the evaluation of sentence and document simplification in German. All texts of this dataset are scraped from the web. All documents were licenced with an open license. The simple-complex sentence pairs are manually aligned.
 This dataset only contains a test set. For additional training and development data, please scrape more data from the web using a [web scraper for text simplification data](https://github.com/rstodden/data_collection_german_simplification) and align the sentences of the documents automatically using, for example, [MASSalign](https://github.com/ghpaetzold/massalign) by [Paetzold et al. (2017)](https://www.aclweb.org/anthology/I17-3001/).
 
-#### Supported Tasks and Leaderboards
+### Supported Tasks and Leaderboards
 
 The dataset supports the evaluation of `text-simplification` systems. Success in this task is typically measured using the [SARI](https://huggingface.co/metrics/sari) and [FKBLEU](https://huggingface.co/metrics/fkbleu) metrics described in the paper [Optimizing Statistical Machine Translation for Text Simplification](https://www.aclweb.org/anthology/Q16-1029.pdf).
 
-#### Languages
+### Languages
 
 The texts in this dataset are written in German (de-de). The texts are in German plain language variants, e.g., plain language (Einfache Sprache) or easy-to-read language (Leichte Sprache).
 
-#### Domains
+### Domains
 The texts are from 6 different domains: fictional texts (literature and fairy tales), bible texts, health-related texts, texts for language learners, texts for accessibility, and public administration texts.
 
-### Dataset Structure
+## Dataset Structure
 
-#### Data Access
+### Data Access
 
 - The dataset is licensed with different open licenses dependent on the subcorpora.
 
-#### Data Instances
+### Data Instances
 - `document-simplification` configuration: an instance consists of an original document and one reference simplification.
-- `sentence-simplification` configuration: an instance consists of an original sentence and one manually aligned reference simplification.
-- `sentence-wise alignment` configuration: an instance consists of original and simplified documents and manually aligned sentence pairs. In contrast to the sentence-simplification configurations, this configuration contains also sentence pairs in which the original and the simplified sentences are exactly the same.
+- `sentence-simplification` configuration: an instance consists of an original sentence and one manually aligned reference simplification. Please see [https://huggingface.co/datasets/DEplain/DEplain-web-sent](https://huggingface.co/datasets/DEplain/DEplain-web-sent).
+- `sentence-wise alignment` configuration: an instance consists of original and simplified documents and manually aligned sentence pairs. In contrast to the sentence-simplification configurations, this configuration contains also sentence pairs in which the original and the simplified sentences are exactly the same. Please see [https://github.com/rstodden/DEPlain](https://github.com/rstodden/DEPlain/tree/main/C__Alignment_Algorithms)
 
 
-#### Data Fields
+### Data Fields
 
 
 | data field                                      | data field description                                                                                |
@@ -107,8 +132,8 @@ The texts are from 6 different domains: fictional texts (literature and fairy ta
 
   
   
-#### Data Splits
-DEplain-web contains a training set, development set and a test set. 
+### Data Splits
+DEplain-web contains a training set, a development set and a test set. 
 The dataset was split based on the license of the data. All manually-aligned sentence pairs with an open license are part of the test set. The document-level test set, also only contains the documents which are manually aligned. For document-level dev and test set the documents which are not aligned or not public available are used. For the sentence-level, the alingment pairs can be produced by automatic alignments (see [Stodden et al., 2023](https://arxiv.org/abs/2305.18939)).
 
 Document-level:
@@ -131,7 +156,7 @@ Sentence-level:
 
 
 
-| **subcorpus**              | **simple**  | **complex** | **domain**  | **description**                                                          | **\# doc.** |
+| **subcorpus**              | **simple**  | **complex** | **domain**  | **description**                                                          | **\ doc.** |
 |----------------------------------|------------------|------------------|------------------|-------------------------------------------------------------------------------|------------------|
 | **EinfacheBücher**          | Plain German               | Standard German / Old German            | fiction          | Books in plain German                                                         | 15               |
 | **EinfacheBücherPassanten** | Plain German               | Standard German / Old German            | fiction          | Books in plain German                                                         | 4                |
@@ -149,7 +174,7 @@ Sentence-level:
 
 
 
-| domain  | avg. | std. | interpretation | \# sents | \# docs |
+| domain  | avg. | std. | interpretation | \ sents | \ docs |
 |------------------|---------------|---------------|-------------------------|-------------------|------------------|
 | bible            | 0.7011        | 0.31          | moderate                | 6903              | 3                |
 | fiction          | 0.6131        | 0.39          | moderate                | 23289             | 3                |
@@ -159,7 +184,7 @@ Sentence-level:
 
 : Inter-Annotator-Agreement per Domain in DEplain-web-manual.
 
-| operation | # documents | percentage |
+| operation |  documents | percentage |
 |-----------|-------------|------------|
 | rehphrase | 863         | 11.73      |
 | deletion  | 3050        | 41.47      |
@@ -172,64 +197,64 @@ Sentence-level:
 
 : Information regarding Simplification Operations in DEplain-web-manual.
 
-### Dataset Creation
+## Dataset Creation
 
-#### Curation Rationale
+### Curation Rationale
 
 Current German text simplification datasets are limited in their size or are only automatically evaluated. 
 We provide a manually aligned corpus to boost text simplification research in German.
 
-#### Source Data
+### Source Data
 
-##### Initial Data Collection and Normalization
+#### Initial Data Collection and Normalization
 The parallel documents were scraped from the web using a [web scraper for text simplification data](https://github.com/rstodden/data_collection_german_simplification).
 The texts of the documents were manually simplified by professional translators. 
 The data was split into sentences using a German model of SpaCy.
 Two German native speakers have manually aligned the sentence pairs by using the text simplification annotation tool [TS-ANNO](https://github.com/rstodden/TS_annotation_tool) by [Stodden & Kallmeyer (2022)](https://aclanthology.org/2022.acl-demo.14/). 
 
-##### Who are the source language producers?
+#### Who are the source language producers?
 The texts of the documents were manually simplified by professional translators. See for an extensive list of the scraped URLs see Table 10 in [Stodden et al. (2023)](https://arxiv.org/abs/2305.18939).
 
-#### Annotations
+### Annotations
 
-##### Annotation process
+#### Annotation process
 
 The instructions given to the annotators are available [here](https://github.com/rstodden/TS_annotation_tool/tree/master/annotation_schema).
 
-##### Who are the annotators?
+#### Who are the annotators?
 
 The annotators are two German native speakers, who are trained in linguistics. Both were at least compensated with the minimum wage of their country of residence.
 They are not part of any target group of text simplification.
 
-#### Personal and Sensitive Information
+### Personal and Sensitive Information
 
 No sensitive data.
 
-### Considerations for Using the Data
+## Considerations for Using the Data
 
-#### Social Impact of Dataset
+### Social Impact of Dataset
 
 Many people do not understand texts due to their complexity. With automatic text simplification methods, the texts can be simplified for them. Our new training data can benefit in training a TS model.
 
-#### Discussion of Biases
+### Discussion of Biases
 
 no bias is known.
 
-#### Other Known Limitations
+### Other Known Limitations
 
 The dataset is provided under different open licenses depending on the license of each website were the data is scraped from. Please check the dataset license for additional information.
 
-### Additional Information
+## Additional Information
 
-#### Dataset Curators
+### Dataset Curators
 
 DEplain-APA was developed by researchers at the Heinrich-Heine-University Düsseldorf, Germany. This research is part of the PhD-program ``Online Participation'', supported by the North Rhine-Westphalian (German) funding scheme ``Forschungskolleg''.
 
-#### Licensing Information
+### Licensing Information
 
 The corpus includes the following licenses: CC-BY-SA-3, CC-BY-4, and CC-BY-NC-ND-4. The corpus also include a "save_use_share" license, for these documents the data provider permitted us to share the data for research purposes.
 
-#### Citation Information
+### Citation Information
 
 
 ```
@@ -247,4 +272,4 @@ The corpus includes the following licenses: CC-BY-SA-3, CC-BY-4, and CC-BY-NC-ND
 }
 ```
 
-This dataset card uses material written by [Juan Diego Rodriguez](https://github.com/juand-r) and [Yacine Jernite](https://github.com/yjernite).
+This dataset card uses material written by [Juan Diego Rodriguez](https://github.com/juand-r) and [Yacine Jernite](https://github.com/yjernite).