This site lists pretrained MarMoT models. The models are free to use for non-commercial research and education. The models can be applied by running:
java -cp marmot.jar marmot.morph.cmd.Annotator\ --model-file de.marmot\ --test-file form-index=0,text.txt\ --pred-file text.out.txt\If text.txt is a text file containing tokenized text in a one token per line format. Sentence boundaries should be marked by an empty line.
This is a sentence . This is another sentence .
The input to the Arabic and Hebrew models should be in the transliterated ASCII format,
described in the documentation of the respective treebank.
Here are two examples:
w >DAf " <n AlEmlyp l AlEwdp b AlbAqyn w Edd hm 193 jndyA l wDE hm fy >mAn , tqdmt kvyrA " .
yyQUOT THIH NQMH W BGDWL yyDOT
The output of the MTE model is in an intermediate format. In order to restore the original annotation you need to run remap_mte.py:
python remap_mte.py text.out.txt text.out.final.txt
The latest MarMoT binaries can be found here.
If you want to run parsing experiments on the SPMRL data sets
we also provide cross-annotated predictions for train, dev and test (marmot_spmrl.tar.bz2) a description is available here.
Acknowledgement: Thanks to Djamé Seddah and Toma Erjavec.
Contact: Thomas Müller (cis page)