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BabelNet-Sememe-Prediction

Code and data of the AAAI-20 paper "Towards Building a Multilingual Sememe Knowledge Base: Predicting Sememes for BabelNet Synsets" [pdf]

Requirements

• Tensorflow-gpu >= 1.13.0
• Python 3.x

Data

This repo contains two types of data.

Annotated BabelSememe Dataset

• BabelSememe Dataset ./BabelSememe/synset_sememes.txt

Experimental Dataset

• Dataset of all POS tags (Noun, Verb, Adj, Adv)

  ./data-all/entitiy2id.txt: All entities and corresponding IDs, one per line.

  ./data-all/relation2id.txt: All relations and corresponding ids, one per line.

  ./data-all/train2id.txt: Training set. All lines are in the format (e1, e2, rel) which indicates there is a relation rel between e1 and e2. The ids of entities and relations are from entitiy2id.txt and relation2id.txt.

  ./data-all/valid2id.txt: Validation set. The lines are all in the format (e1, e2, rel) which indicates there is a relation rel between e1 and e2. The ids of entities and relations are from entitiy2id.txt and relation2id.txt.

  ./data-all/test2id.txt: Test set. The lines are all in the format (e1, e2, rel) which indicates there is a relation rel between e1 and e2. The ids of entities and relations are from entitiy2id.txt and relation2id.txt.

• Dataset of Nouns

  The format of the noun dataset is the same as the all dataset.

  ./data-noun/entitiy2id.txt

  ./data-noun/relation2id.txt

  ./data-noun/train2id.txt

  ./data-noun/valid2id.txt

  ./data-noun/test2id.txt

• Synset embeddings from NASARI

  ./SPBS-SR/synset_vec.txt

Models

SPBS-SR

Usage

Commands for training and testing models:

cd ./SPBS-SR/
python EvalSememePre_SPWE.py 1

SPBS-RR

Usage

Commands for training and testing models:

cd ./SPBS-RR/src/
bash train.sh

Note: Test results are recorded in the training log.

Ensemble

Usage

After training the above two models, copy the output files ./SPBS-RR/sememePre_TransE.txt and ./SPBS-SR/sememePre_SPWE.txt to the Ensemble directory, and then run the Ensemble model with the following command:

cd ./Ensemble/
python Ensemble.py

Cite

If you use any code or data, please cite this paper

@article{qi2019towards,
  title={Towards Building a Multilingual Sememe Knowledge Base: Predicting Sememes for BabelNet Synsets},
  author={Qi, Fanchao and Chang, Liang and Sun, Maosong and Ouyang, Sicong and Liu, Zhiyuan},
  journal={arXiv preprint arXiv:1912.01795},
  year={2019}
}