The “jump and stay” method to discover proper verb centered constructions in corpus lattices

What is this all about?

The “jump and stay” method is described here: The “jump and stay” method to discover proper verb centered constructions in corpus lattices

The foundation, the double cube model is described here: A lattice based algebraic model for verb centered constructions

Usage

Please type:

make all

to run the algorithm (described in section 5)

• using verb hagy (allow) on train data to get the full output which Fig. 4 is based on (in file named hagy.train.out3); and
• using verbs húz (draw/pull) and vet (cast/throw) on test data to get the results presented in Table 1. in the [paper](RANLP 2019...) (in files huz.test.out3.pVCC and vet.test.out3.pVCC).

Tested on Debian Linux. (May work on other operation systems...)

Requirements: python 3 make uni2ascii (if not available: sudo apt-get install uni2ascii)

Language independency

This method is considered language independent. See: https://github.com/sassbalint/double-cube-jump-and-stay-multilingual

License

If you want to use this, please cite the above papers and contact me. :) No warranty, sorry.