Context

Bio-medical texts have a lot of information which can be used for developments in the medical field. Traditionally, domain experts used to manually extract such information. Automating this information extraction task can help speed up progress in the field.
To name a few use cases of bio-medical events, they show the effects of drugs on a person. They can also be used to identify certain medical conditions in a person.
Hence automating extraction of events from bio-medical texts is very beneficial

Content

The dataset is just a simplified version of the event annotated GENIA dataset derived from the version available in TEES

It consists of the original bio-medical text, labelled trigger words, location of trigger word in the text and the event type associated with the trigger word
There are 3 sets of data (train (8k+ sentences), devel (about 3k sentences) and test (about 3k sentences)).
Each set has 4 columns namely "Sentence", "TriggerWord", "TriggerWordLoc" and "EventType", capturing the original bio-medical text, trigger words in the sentence, location of the trigger words in the sentence and the event type associated with the trigger words respectively.

Acknowledgements

The dataset is just a simplified version of the event annotated GENIA dataset derived from the version available in TEES
The original source dataset is from BionLP Shared Task 2011
A complete unprocessed version seems to be present in genia-event-2011 dataset too

For TEES licensing information please refer this link
For GENIA dataset licensing information, please refer the file "GE11-LICENSE" present beside the data files (.csv) in this kaggle dataset

Photo Credits: Louis Reed on Unsplash