Update README.md

README.md

@@ -2,73 +2,50 @@
 annotations_creators:
 - expert-generated
 language_creators:
-- expert-generated
+- found
 languages:
 - en-US
 licenses: []
 multilinguality:
 - monolingual
-pretty_name: sciarg
-size_categories: []
-source_datasets:
-- original
 task_categories:
-- token-classification
+- structure-prediction
 task_ids:
 - parsing
 ---
 
-# Dataset Card for sciarg
+# Information Card for Brat
 
 ## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks](#supported-tasks-and-leaderboards)
+- [Description](#description)
+  - [Summary](#summary)
   - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
+ - [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)
+- [Annotation Information](#annotation-information)
 - [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
   - [Licensing Information](#licensing-information)
   - [Citation Information](#citation-information)
 
-## Dataset Description
+## Description
 
-- **Homepage:** https://github.com/anlausch/ArguminSci
-- **Repository:** https://github.com/anlausch/ArguminSci
-- **Paper:** https://aclanthology.org/W18-5206.pdf
+- **Homepage:** https://brat.nlplab.org
+- **Paper:** https://aclanthology.org/E12-2021/
 - **Leaderboard:** [Needs More Information]
 - **Point of Contact:** [Needs More Information]
 
-### Dataset Summary
-
-This dataset is an extension of the Dr. Inventor corpus (Fisas et al., 2015, 2016) with an annotation layer containing fine-grained argumentative components and relations. It is the first argument-annotated corpus of scientific publications (in English), which allows for joint analyses of argumentation and other rhetorical dimensions of scientific writing.
+### Summary
 
-### Supported Tasks and Leaderboards
-
-[Needs More Information]
+Brat is an intuitive web-based tool for text annotation supported by Natural Language Processing (NLP) technology. BRAT has been developed for rich structured annota- tion for a variety of NLP tasks and aims to support manual curation efforts and increase annotator productivity using NLP techniques. brat is designed in particular for structured annotation, where the notes are not free form text but have a fixed form that can be automatically processed and interpreted by a computer.
 
 ### Languages
 
-English
+English.
 
 ## Dataset Structure
-
 ### Data Instances
-
 [Needs More Information]
-
 ### Data Fields
 ```
 -context: html content of data file as string
@@ -81,73 +58,34 @@ English
 -normalizations:
 -notes:
 ```
-### Data Splits
-
-train : 40 instances
-
-## Dataset Creation
-
-### Curation Rationale
-
-[Needs More Information]
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[Needs More Information]
-
-#### Who are the source language producers?
-
-[Needs More Information]
-
-### Annotations
 
-#### Annotation process
 
-Annotation guidelines can be found [here](http://data.dws.informatik.uni-mannheim.de/sci-arg/annotation_guidelines.pdf).
-
-#### Who are the annotators?
-
-[Needs More Information]
-
-### Personal and Sensitive Information
-
-[Needs More 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]
+## Annotation Information
+Annotations created in brat are stored on disk in a standoff format: annotations are stored separately from the annotated document text, which is never modified by the tool. For each text document in the system, there is a corresponding annotation file. The two are associatied by the file naming convention that their base name (file name without suffix) is the same: for example, the file DOC-1000.ann contains annotations for the file DOC-1000.txt. More information can be found [here](https://brat.nlplab.org/standoff.html).
 
 ## Additional Information
 
-### Dataset Curators
-
-[Needs More Information]
-
 ### Licensing Information
 
 [Needs More Information]
 
 ### Citation Information
+
 ```
-@inproceedings{lauscher2018b,
-    title = {An argument-annotated corpus of scientific publications},
-    booktitle = {Proceedings of the 5th Workshop on Mining Argumentation},
-    publisher = {Association for Computational Linguistics},
-    author = {Lauscher, Anne and Glava\v{s}, Goran and Ponzetto, Simone Paolo},
-    address = {Brussels, Belgium},
-    year = {2018},
-    pages = {4046}
-  }
-  ```
+@inproceedings{stenetorp-etal-2012-brat,
+    title = "brat: a Web-based Tool for {NLP}-Assisted Text Annotation",
+    author = "Stenetorp, Pontus  and
+      Pyysalo, Sampo  and
+      Topi{\'c}, Goran  and
+      Ohta, Tomoko  and
+      Ananiadou, Sophia  and
+      Tsujii, Jun{'}ichi",
+    booktitle = "Proceedings of the Demonstrations at the 13th Conference of the {E}uropean Chapter of the Association for Computational Linguistics",
+    month = apr,
+    year = "2012",
+    address = "Avignon, France",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/E12-2021",
+    pages = "102--107",
+}
+```