https://github.com/dair-iitd/kbi-regex

https://github.com/dair-iitd/kbi-regex

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• Host: GitHub
• URL: https://github.com/dair-iitd/kbi-regex
• Owner: dair-iitd
• Created: 2021-09-15T04:44:15.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2022-09-12T16:08:23.000Z (over 2 years ago)
• Last Synced: 2024-08-02T19:37:01.092Z (5 months ago)
• Language: Python
• Size: 23.4 KB
• Stars: 1
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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• awesome-logical-query - GitHub - no actual data dumps are present :( (📈 Datasets and Benchmarking / Regex Queries)

README

        
# KBI-Regex

This repository contains code and data for reproducing the results of our paper:

Vaibhav Adlakha, Parth Shah, Srikanta Bedathur, Mausam. [Regex Queries over Incomplete Knowledge Bases](https://www.akbc.ws/2021/papers/4YQVfA5vEJS)

To cite this work, please use the following citation:

```

@inproceedings{

adlakha2021regex,

title={Regex Queries over Incomplete Knowledge Bases},

author={Vaibhav Adlakha and Parth Shah and Srikanta J. Bedathur and Mausam .},

booktitle={3rd Conference on Automated Knowledge Base Construction},

year={2021},

url={https://openreview.net/forum?id=4YQVfA5vEJS}

}

```

## Downloading Datasets

The paper introduces two datasets for regex queries over incomplete knowledge bases - FB15K-Regex and Wiki100-Regex. These datasets are available to be downloaded from the following links - 

1. [FB15K-Regex](https://zenodo.org/record/7071856/files/fb15k_regex_data.zip)

2. [Wiki100-Regex](https://zenodo.org/record/7071856/files/wiki_v2_regex_data.zip)

Each dataset is a `.zip` file. This needs to be placed in a `cache/raw-datasets` directory within the project directory. The directory structure should look like the following:

```

kbi-regex

     |___ cache

            |___ raw-datasets

                     |____ fb15k_regex_data.zip

                     |____ wiki_v2_regex_data,zip

```

The zip files will be unpacked and encoded when the code is run for the first time, and will be used for subsequent runs.

## Running Models

To run the model, we first need to install the repository as a package. From the project directory, run the following command:

```

pip install --no-index --no-deps -e .

```

Use the following command to run RotatE-Box (Free parameter + Aggregation) on FB15K-Regex

```

python main.py \

    --model RotatE --box \

    --kleene_plus_op free_param \

    --dataset fb15k \

    -dim 800 \

    --query_types "0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 21" \

    --do_train \

    --learning_rate 1e-4 \

    --lr_schedule half \

    --truncate_loss \

    --batch_size 1024 \

    --negative_sample_count 256 \

    --max_epochs 500 \

    --resume_from_checkpoint  \

    --seed 0 \

    --num_workers 8 \

    --save_dir 

```

## Contact

For queries and clarifications please contact **vaibhav.adlakha (at) mila (dot) quebec**