Named Entity Recognition for annotated corpus using GMB(Groningen Meaning Bank) corpus for entity classification with enhanced and popular features by Natural Language Processing applied to the data set.

Content

The dataset an extract from GMB corpus which is tagged, annotated and built specifically to train the classifier to predict named entities such as name, location, etc. GMB is a fairly large corpus with a lot of annotations. Unfortunately, GMB is not perfect. It is not a gold standard corpus, meaning that it’s not completely human annotated and it’s not considered 100% correct. The corpus is created by using already existed annotators and then corrected by humans where needed.
The attached dataset is in tab separated format, the goal is to create a good model to classify the Tag column. The data is labelled using the IOB tagging system.
Here are the following classes in the dataset -
geo = Geographical Entity
org = Organization
per = Person
gpe = Geopolitical Entity
tim = Time indicator
art = Artifact
eve = Event
nat = Natural Phenomenon