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Classifier & sequence-tagger for rhetorical function expressions (moves) in academic articles

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Introduction

This is the implementation of my masters thesis, Identification and Classification of Rhetorical Function Categories. This repository includes the code for the classifier and the sequence tagger, baseline models, the pre- and post-processing, and the analyses.

If you find the implementation helpful, please cite my thesis:

@mastersthesis{chen2023rfe,
  author  = "Li-Kuang Chen",
  title   = "Identification and Classification of Rhetorical Function Categories",
  school  = "National Tsing Hua University",
  year    = "2023"
}

Setup

The python version used is 3.8.10, but python 3.9.6 works fine too.

We recommend creating a virtual environment for the experiments:

python3.8 -m venv .env
source .env/bin/activate

After you createrd the virtual environment, clone the project and install necessary packages:

git clone https://github.com/LKChenLK/RFE.git
cd RFE
pip install -r requirements.txt

Data

The pre-processed data is available here. Please see data for further details.

Experiments

We used AllenNLP to build the models and run experiments. To be able to use AllenNLP, you need to install rfe as a package. Run

pip install -e .

For details in reproducing the experiments in the paper, see experiments.

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Classifier & sequence-tagger for rhetorical function expressions (moves) in academic articles

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