🏷️ Part-of-speech tagging ✍️

This repository contains a project realized for an assignment of the Natural Language Processing course of the Master's degree in Artificial Intelligence, University of Bologna.

Description

Part-of-speech (POS) tagging is a popular NLP task which refers to categorizing words in a text (corpus) in correspondence with a particular part of speech, depending on the definition of the word and its context.

To tackle this problem, different types of Recurrent Neural Networks and parameters are been used, namely BiLSTM, Bi-GRU, double BiLSTM with different combinations of fully connected layers. The input was embedded using GloVE embeddings, and the Out-Of-Vocabulary words were randomly instantiated. After sufficient hyperparameter tuning, the best models were BiLSTM and BiGRU, and they achieved Macro-F1 scores of 0.6183 and 0.6117 on the validation set.

Dataset

For this experiment, the Dependency Parsed Treebank dataset is used. It contains 199 documents annotated, but in oder to achieve better results each document is been splitted into sentences. The train-val-test split proprortin is 50%-25%-25%.

Request and solution proposed

The task to comply with is described in the assignment description. In order to have a better understanging of our proposed solution, take a look to the notebook and the report.

Results

The metric which has been used to compare models is the macro F1 score with the validation set, results are the following:

Metric	BiLSTM	BiGRU	2 BiLSTM + Dense	BiLSTM + 2 Dense
Accuracy val	0.8457	0.8362	0.7564	0.7907
F1 score val	0.6183	0.6117	0.5094	0.4840
F1 score test	0.6246	0.6062	not tested	not tested

This is an example of the prediction made by the BiGRU model on a test sentence:

Original sentence:  ['but' 'courts' 'quickly' 'tumbled' 'down' 'a' 'slippery' 'slope' '.']
Original POS tagging:  ['CC' 'NNS' 'RB' 'VBD' 'IN' 'DT' 'JJ' 'NN' '.']
Predicted POS tagging:  ['CC' 'NNS' 'RB' 'VBD' 'RP' 'DT' 'JJ' 'NN' '.']

Resources & Libraries

• scikit-learn
• Tensorflow + Keras

Versioning

We use Git for versioning.

Group members

Reg No.	Name	Surname	Email	Username
1005271	Giuseppe	Boezio	giuseppe.boezio@studio.unibo.it	giuseppeboezio
983806	Simone	Montali	simone.montali@studio.unibo.it	montali
997317	Giuseppe	Murro	giuseppe.murro@studio.unibo.it	gmurro

License

This project is licensed under the MIT License - see the LICENSE file for details