Update README.md

README.md

@@ -30,4 +30,160 @@ configs:
     path: data/train-*
   - split: test
     path: data/test-*
+task_categories:
+- token-classification
+language:
+- en
+tags:
+- biomedical
+- clinical-trial
+- scientific-articles
+size_categories:
+- 1K<n<10K
 ---
+
+# Dataset Card for Dataset Name
+
+Corpus for token classification of primary and secondary outcomes in scientific articles sentences, in BIO format.
+
+## Dataset Details
+
+### Dataset Description
+
+Filtered the [EBM-NLP](https://github.com/bepnye/EBM-NLP) corpus Outcomes subset and did the following processing: 
+* split examples into sentences and get the entities for each sentence
+* verify in each sentences mentions of primary and secondary outcomes using regular expression (with synonyms)
+* tagged all outcomes according to type when the regex was found in a sentence
+* removed entity tags for all sentences that were not detected as containing primary or secondary outcome
+* kept the examples at sentence level
+* kept original train/test set
+
+
+Then added [data from A. koroleva](https://github.com/aakorolyova/DeSpin-2.0/tree/main/data/Primary_Outcomes) on primary outcomes (manually annotated corpus).
+Part of this data is 
+
+Then added manually annotated data from a study on primary outcome switching in colorectal cancer articles (this data is only used in test set).
+
+Finally as the filtered EBM-NLP contained a lot of sequences without entities in the end, we sampled from these sequences so that we have an equal number of sequences with and without entities, in train and test set.
+
+- **Curated by:** Mathieu Laï-king
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Language(s) (NLP):** English
+- **License:** None
+
+### Dataset Sources [optional]
+
+From 2 existing corpus one from A. Koroleva and the other is EBM-NLP.
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+
+### Direct Use
+
+Fine tuning NER models
+
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
+
+[More Information Needed]
+
+## Dataset Structure
+
+<!-- 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]
+
+## Dataset Creation
+
+### Curation Rationale
+
+<!-- Motivation for the creation of this dataset. -->
+
+[More Information Needed]
+
+### Source Data
+
+<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
+
+#### 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. -->
+
+[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. -->
+
+#### 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]
+
+#### Who are the annotators?
+
+<!-- This section describes the people or systems who created the annotations. -->
+
+[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]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[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.
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Dataset Card Authors [optional]
+
+[More Information Needed]
+
+## Dataset Card Contact
+
+[More Information Needed]