Trance parser model for Korean: Sejong treebank

<p>Trance parsing model + Embedding vector.</p> <p>See https://github.com/tarowatanabe/trance for the parser and its usage. We also provide parsing and learning scripts for the Trance parser that we used for the paper; </p> <p>1/ parsing model: ptb_train.txt.model-d100.tar.gz        </p> <p>2/ embedding vector: embedding-d100.vec.gz</p> <p>3/ trance parser parsing script: trance-parsing.sh</p> <p>4/ trance parser (batch) learning script: trance-training-batch.sh</p> <p>5/ test.txt (gold file) and test.txt.leaf is for the parser input. </p> <p>## Jungyeul Park, A Note on Constituent Parsing for Korean Using the Sejong Treebank (submitted to TALLIP). October 2017.</p> <p>See https://github.com/jungyeul/tallip-sjtree-parsing for more detail. </p

MaltParser model for Korean: Sejong treebank

<p>MaltParser model for Korean:  Sejong treebank</p> <p>Jungyeul Park, Jeen-Pyo Hong, and Jeong-Won Cha (2016). Korean Language Resources for Everyone. In Proceedings of the 30th Pacific Asia Conference on Language, Information and Computation (PACLIC 30). Seoul, Korea. [pdf]</p> <p>@inproceedings{park-hong-cha:2016:PACLIC, <br> address = {Seoul, Korea}, <br> author = {Park, Jungyeul and Hong, Jeen-Pyo and Cha, Jeong-Won}, <br> booktitle = {Proceedings of the 30th Pacific Asia Conference on Language, Information and Computation (PACLIC 30)}, <br> pages = {49--58}, <br> title = {{Korean Language Resources for Everyone}}, <br> year = {2016} <br> }</p> <p>It requires Espresso's POS tagging results for input. Espresso is available at https://zenodo.org/record/884606 </p

Sentence Boundary Data Set for French

<p>Jungyeul Park (in preparation). New Approaches for Sentence Boundary Detection - From data curation to building applications for French. Intended to submit to Language Resources and Evaluation, Springer. (May, 2018); </p> <p> </p> <p>See also https://github.com/jungyeul/french-sbd</p> <p> </p