This is the open-source code of the EMNLP 2018 paper Cross-lingual Lexical Sememe Prediction [pdf].

Sememes are defined as the minimum semantic units of human languages. As important knowledge sources, sememe-based linguistic knowledge bases have been widely used in many NLP tasks. However, most languages still do not have sememe-based linguistic knowledge bases. Thus we present a task of cross-lingual lexical sememe prediction (CLSP), aiming to automatically predict sememes for words in other languages. We propose a novel framework to model correlations between sememes and multi-lingual words in low-dimensional semantic space for sememe prediction. Experimental results on real-world datasets show that our proposed model achieves consistent and significant improvements as compared to baseline methods in cross-lingual sememe prediction.

bash run.sh

To change the training corpus, please just switch the -mono-train1 and -mono-train2 parameters in bash.sh. Notice that lang1 refers to the source language and lang2 refers to the target language.

If the codes or datasets help you, please cite the following paper:

@InProceedings{qi2018cross,
  Title      = {Cross-lingual lexical sememe prediction},
  Author     = {Qi, Fanchao and Lin, Yankai and Sun, Maosong and Zhu, Hao and Xie, Ruobing and Liu, Zhiyuan},
  Booktitle  = {Proceedings of EMNLP},
  Year       = {2018},
}