A compound splitter based on the semantic regularities in the vector space of word embeddings. For more information see this presentation or our paper.

To use this tool with standard settings, do the following:

$ wget https://raw.githubusercontent.com/jodaiber/semantic_compound_splitting/master/decompound_dict.py https://raw.githubusercontent.com/jodaiber/semantic_compound_splitting/master/models/de.dict
$ python decompound_dict.py de.dict < your_file
Verhandlungs Ablauf

The file your_file should contain tokenized sentences.

--drop_fugenlaute If this flag is set, Fugenlaute (infixes such as -s, -es) are dropped from the final words.

$ python decompound_dict.py de.dict --drop_fugenlaute < your_file
Verhandlung Ablauf

--lowercase Lowercase all words.

--restore_case True/False Restore the case of the parts of the compound (words will take the case of the original word). Default: True

--ignore_case Ignores case: all input words should be lowercase.

If you use this splitter in your work, please cite:

@inproceedings{daiber2015compoundsplitting,
  title={Splitting Compounds by Semantic Analogy},
  author={Daiber, Joachim and Quiroz, Lautaro and Wechsler, Roger and Frank, Stella},
  booktitle={Proceedings of the 1st Deep Machine Translation Workshop},
  editor = {Jan Hajič and António Branco},
  pages={20--28},
  year={2015},
  isbn = {978-80-904571-7-1},
  publisher={Charles University in Prague, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics},
  url={http://jodaiber.github.io/doc/compound_analogy.pdf}
}

• Roger Wechsler, University of Amsterdam
• Lautaro Quiroz, University of Amsterdam
• Joachim Daiber, ILLC, University of Amsterdam

Apache 2.0