named-entity-recognition-research's Introduction

Named Entity Recognition research

Dataset description

Every row in the dataset contains a complete sentence and list of NER tags for each word in the sentence.

Each NER tag belongs to the one of the following 16 types:

Key	Description
B-PER	Name of a person
I-PER	Part of named entity that is the name of a person
B-GEO	Geographical entity
I-GEO	Part of named entity that is a geographical entity
B-ART	Title of a creative work
I-ART	Part of named entity that is the title of a creative work
B-GPE	Geopolitical entity (country, region, etc.)
I-GPE	Part of named entity that is a geopolitical entity
B-EVE	Named event or occurrence
I-EVE	Part of named entity that is a named event or occurrence
B-NAT	Nationality, religious affiliation, or political group
I-NAT	Part of named entity that is nationality, religious affiliation, or political group
B-ORG	Name of an organization or group
I-ORG	Part of named entity that is the name of an organization or group
B-TIM	Time expression
I-TIM	Part of named entity that is a time expression

Data sample:

You can see this dataset in data/ner.csv.

How to run the visualizer?

Firstly, you should install all requarements. For that purpose, you should run the following command:

pip install -r requirements.txt

After that, you simply run the visualizer/app.py and program run our application on your localhost.

Next, you will see like this in your python console:

* Serving Flask app 'app'
 * Debug mode: on
WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
 * Running on http://127.0.0.1:5000
Press CTRL+C to quit
...

Now, you just should follow the link in console. Finally, you can use the our app.

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