Implementation of "Unsupervised joke generation from big data" (ACL 2013)
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Implementation of Japanese version of "Unsupervised joke generation from big data" (ACL 2013)


You have to prepare Japanese WordNet sqlite3 database. Download from here ( Put wnjpn.db in the same directory as the scripts.

To train the model, run this command. $ python --corpus [your n-gram file]

N-gram file should consist of the line which has the format as follows: [token-1][token-2]...[token-n][count]

Google N-gram corpus follows this format, so you can use it as corpus.


To generate the nazokake, run this command.

$ python --model [model generated by training mode]

Example Output


Sasa Petrovic and David Matthews, "Unsupervised joke generation from big data," The 51st Annual Meeting of the Association for Computational Linguistics - Short Papers (ACL Short Papers 2013), Sofia, Bulgaria, August 4-9, 2013

yanbe.diff, "Frontend program to search from Japanese WordNet database." (Japanese: 日本語WordNetのデータベースを探索するフロントエンドプログラム)