Update README.md

README.md

@@ -73,7 +73,7 @@ LR-Sum is released under a Creative Commons license (CC BY 4.0), making it one o
 
 - **Curated by:** BLT Lab: Chester Palen-Michel and Constantine Lignos
 - **Shared by:** Chester Palen-Michel
-- **Language(s) (NLP): Albanian, Amharic, Armenian, Azerbaijani, Bengali, Bosnian, Burmese, Chinese, English, French, Georgian, Greek, Haitian Creole, Hausa, Indonesian, Khmer, Kinyarwanda, Korean, Kurdish, Lao, Macedonian, Northern Ndebele, Pashto, Persian, Portuguese, Russian, Serbian, Shona, Somali, Spanish, Swahili, Thai, Tibetan, Tigrinya, Turkish, Ukrainian, Urdu, Uzbek, Vietnamese
+- **Language(s) (NLP):** Albanian, Amharic, Armenian, Azerbaijani, Bengali, Bosnian, Burmese, Chinese, English, French, Georgian, Greek, Haitian Creole, Hausa, Indonesian, Khmer, Kinyarwanda, Korean, Kurdish, Lao, Macedonian, Northern Ndebele, Pashto, Persian, Portuguese, Russian, Serbian, Shona, Somali, Spanish, Swahili, Thai, Tibetan, Tigrinya, Turkish, Ukrainian, Urdu, Uzbek, Vietnamese
 - **License:** CC-BY 4.0
 
 ### Dataset Sources [optional]
@@ -81,8 +81,9 @@ LR-Sum is released under a Creative Commons license (CC BY 4.0), making it one o
 Multilingual Open Text v1.6
 which is a collection of newswire text from Voice of America (VOA).
 
-- **Repository:** https://github.com/bltlab/lr-sum
-- **Paper:** https://aclanthology.org/2023.findings-acl.427/
+- **Paper:** [https://aclanthology.org/2023.findings-acl.427/](https://aclanthology.org/2023.findings-acl.427/)
+- **Repository:** [https://github.com/bltlab/lr-sum](https://github.com/bltlab/lr-sum)
+
 
 ## Uses
 
@@ -99,71 +100,64 @@ This dataset only includes newswire text, so models trained on the data may not
 
 
 ## Dataset Structure
+Each field is a string: 
 
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-
-[More Information Needed]
+  'id': Article unique id
+  'url': URL for the news article
+  'title': The title of the news article
+  'summary': The summary of the article
+  'text': The full text of the news article not including title
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
+Research in automatic summarization for less resourced languages.
 
 ### Source Data
 
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
+Voice of America (VOA)
 
 #### Data Collection and Processing
 
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
+See our [paper](https://aclanthology.org/2023.findings-acl.427/) for details on collection and processing. 
 
-[More Information Needed]
 
 #### Who are the source data producers?
 
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
-
-### Annotations [optional]
-
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
+Voice of America (VOA)
 
 #### Annotation process
 
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-
-[More Information Needed]
+The summaries are found in news article meta data. More detail about the curation process can be found in our paper.
 
 #### Who are the annotators?
 
-<!-- This section describes the people or systems who created the annotations. -->
+The summaries are found in the news article meta data. The authors of the summaries are authors and staff for VOA.
 
-[More Information Needed]
 
 #### Personal and Sensitive Information
 
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-
-[More Information Needed]
+The only sensative personal information would be information already published in news articles on VOA. 
+See [VOA's mission and values](https://www.insidevoa.com/p/5831.html#:~:text=VOA%20has%20a%20legal%20obligation,sites%20at%20the%20earliest%20opportunity.)
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+The content in this dataset is newswire.
+See [VOA's mission and values](https://www.insidevoa.com/p/5831.html#:~:text=VOA%20has%20a%20legal%20obligation,sites%20at%20the%20earliest%20opportunity.) for more detail about the journalistic integrity and policy. 
 
-[More Information Needed]
 
 ### Recommendations
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
+The data is newswire text. Training text generation models on this dataset will have similar risks and limitations to other text generation models including hallucinations and potentially inaccurate statements. 
+For some languages that have fewer examples, issues with text generation models are likely to be more pronounced.
+The dataset is primarily released for research despite having a permissive license. 
+We encourage users to thoroughly test and evaluate any models trained using this data before putting them into production environments. 
 
 ## Citation
 
+If you make use of this dataset, please cite our paper using this bibtex: 
+
 **BibTeX:**
 ```
 @inproceedings{palen-michel-lignos-2023-lr,
@@ -185,14 +179,10 @@ Users should be made aware of the risks, biases and limitations of the dataset.
 }
 ```
 
-**APA:**
-
-Palen-Michel, C. & Lignos, C. (2023). LR-Sum: Summarization for Less-Resourced Languages. In Findings of the Association for Computational Linguistics: ACL 2023, pages 6829–6844, Toronto, Canada. Association for Computational Linguistics.
-
-## Dataset Card Authors [optional]
+## Dataset Card Authors
 
-Chester Palen-Michel
+Chester Palen-Michel [@cpalenmichel](https://github.com/cpalenmichel)
 
 ## Dataset Card Contact
 
-Chester Palen-Michel
+Chester Palen-Michel [@cpalenmichel](https://github.com/cpalenmichel)