Named Entity Recognition Using Decision Trees

This repositiory covers how to extract the Named Entities in the SemEval2010 - Task 8 Dataset. You can look up the Dataset here. Also, the SemEval2010 - Task 8 statement can be read here.

Quickstart and Summary

For the implementation, the task has been divided into two parts:

Part 1 and Part 2:

Creation of the Corpus Reader Class to parse the data from the dataset into a DataFrame for the Model.

Some Common NLP Tasks such as: POS Identification, Dependency Parsing, Full Synctactic Parsing, HyperNym, HoloNym, MeroNym and HypoNym Extraction, etc.

Part 3:

Creation of the Decision Tree Model to perform the Relation Classification and Identification.

Steps to Run the Code:

For Task 1 & 2:

1. Download the Submission. The code file for this task is called, Task1_2Demo.py.

2. Create a File called "test_sentence.txt" containing the test sentences for which you want to run the Task 1 and Task 2.

3. Save this file in the same directory as the code, i.e., /Code.

4. run

pip install -r requirements.txt

run

python -m spacy download en_core_web_sm

To Download all packages and dependencies

5. Run the Code as python Task1_2Demo.py and you will see all the outputs printed on the console or on the IDE you are using.

6. This code can also be run on Google Colab as:

a) Open Google Colab, upload the test_sentence.txt

b) Import the Task1_2Demo.ipynb on Colab. You should be able to run all the tasks.

c) The Notebook Link is clickable here:

For Task 3:

1. Open the IDE of your choice. And run the Command python -m spacy download en_core_web_sm

2. Download the SemEval dataset available on E-Learning and put in the same directory, i.e, /Code and name it as semeval_train.txt

3. Put all your test sentences in a file called semeval_test.txt or to run this on the entire test set, Download the file available on e-learning and rename as semeval_test.txt

4. Once you copy the test sentences, just make sure that you have run the pip install step as before.

5. Run the code as python Task3Demo.py