README.md

PLOD: An Abbreviation Detection Dataset

This is the repository for PLOD Dataset submitted to LREC 2022. The dataset can help build sequence labelling models for the task Abbreviation Detection.

Dataset

We provide two variants of our dataset - Filtered and Unfiltered. They are described in our paper here.

1. The Filtered version can be accessed via Huggingface Datasets here and a CONLL format is present here.
   

2. The Unfiltered version can be accessed via Huggingface Datasets here and a CONLL format is present here.
   

Installation

We use the custom NER pipeline in the spaCy transformers library to train our models. This library supports training via any pre-trained language models available at the :rocket: HuggingFace repository.
Please see the instructions at these websites to setup your own custom training with our dataset.

Model(s)

The working model is present here at this link.
On the link provided above, the model can be used with the help of the Inference API via the web-browser itself. We have placed some examples with the API for testing.

Usage (in Python)

You can use the HuggingFace Model link above to find the instructions for using this model in Python locally.