Official code for the paper "Evaluating Neural Word Embeddings for Sanskrit".

EvalSan: Evaluation Toolkit for Sanskrit Embeddings

SanEval is a toolkit for evaluating the quality of Sanskrit embeddings. We assess their generalization power by using them as features on a broad and diverse set of tasks. We include a suite of 4 intrinsic tasks which evaluate on what linguistic properties are encoded in word embeddings. Our goal is to ease the study and the development of general-purpose fixed-size word representations for Sanskrit.

Dependencies

This code is written in python. The dependencies are:

• Python 3.6

pip install -r requirements.txt

Evaluation tasks

Intrinsic tasks

• SanEval includes a series of Intrinsic tasks to evaluate what linguistic properties are encoded in your word embeddings.
• We use SLP1 transliteration scheme for our data. You can change it to another scheme using this code.

Task	Metric	#dev	#test
Relatedness	F-score	4.5k	9k
Similarity	Accuracy	na	3k
Categorization Syntactic	Purity	na	1.1k
Categorization Semantic	Purity	na	150
Analogy Syntactic	Accuracy	na	10k
Analogy Semantic	Accuracy	na	6.4k

Pretrained models

• You can download the pretrained models from this link. README.md is given for each model.
• Place the models folder in the parent directory path.
• Pretrained vectors can be downloaded from this link. Place this folder in EvalSan/evaluations/Intrinsic/ path. This vectors are being used in evaluation script.

How to train the models

Please refer to the models folder for more details.

bash train_embeddings.sh

How to run evaluation

To evaluate your word embeddings, run the following command:

bash run_SanEval.sh

Citation

If you use our tool, we'd appreciate if you cite the following paper:

@inproceedings{sandhan-etal-2023-evaluating,
    title = "Evaluating Neural Word Embeddings for {S}anskrit",
    author = "Sandhan, Jivnesh  and
      Paranjay, Om Adideva  and
      Digumarthi, Komal  and
      Behra, Laxmidhar  and
      Goyal, Pawan",
    booktitle = "Proceedings of the Computational {S}anskrit {\&} Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
    month = jan,
    year = "2023",
    address = "Canberra, Australia (Online mode)",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.wsc-csdh.2",
    pages = "21--37",
}

License

This project is licensed under the terms of the Apache license 2.0.