Codes for "Template-free Prompt Tuning for Few-shot NER".

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Deep LearningEntLM
Overview

EntLM

The source codes for EntLM.

Dependencies:

Cuda 10.1, python 3.6.5

To install the required packages by following commands:

$ pip3 install -r requirements.txt

To download the pretrained bert-base-cased model:

$ cd pretrained/bert-base-cased/
$ sh download_bert.sh

Few-shot Experiment

Run the few-shot experiments on CoNLL 5-shot with:

sh scripts/run_conll.sh

By default, this runs 4 rounds of experiments for each of the sampled datasets. You can also run 10/20/50-shot experiments by editing the line FILE_PATH=dataset/conll/5shot/ in scripts/run_conll.sh .

Label word selection

You can run the label word selection process by:

sh scripts/count_freq.sh

This will build a label_map file such as dataset/conll/label_map_timesup_ratio0.6_multitoken_top6.json in the dataset path.

You can try different method by changing "--sort_method" to ["LM", "data", "timesup"].

Or you can try different ratio/virtual_number by changing "--filter_ratio" and "--top_k_num".

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