Slavic Forest, Norwegian Wood (models)

Rosa, Rudolf; Zeman, Daniel; Mareček, David; Žabokrtský, Zdeněk

dc.contributor.author	Rosa, Rudolf
dc.contributor.author	Zeman, Daniel
dc.contributor.author	Mareček, David
dc.contributor.author	Žabokrtský, Zdeněk
dc.date.accessioned	2017-03-24T16:01:36Z
dc.date.available	2017-03-24T16:01:36Z
dc.date.issued	2017-01-28
dc.identifier.uri	http://hdl.handle.net/11234/1-1971
dc.description	Trained models for UDPipe used to produce our final submission to the Vardial 2017 CLP shared task (https://bitbucket.org/hy-crossNLP/vardial2017). The SK model was trained on CS data, the HR model on SL data, and the SV model on a concatenation of DA and NO data. The scripts and commands used to create the models are part of separate submission (http://hdl.handle.net/11234/1-1970). The models were trained with UDPipe version 3e65d69 from 3rd Jan 2017, obtained from https://github.com/ufal/udpipe -- their functionality with newer or older versions of UDPipe is not guaranteed. We list here the Bash command sequences that can be used to reproduce our results submitted to VarDial 2017. The input files must be in CoNLLU format. The models only use the form, UPOS, and Universal Features fields (SK only uses the form). You must have UDPipe installed. The feats2FEAT.py script, which prunes the universal features, is bundled with this submission. SK -- tag and parse with the model: udpipe --tag --parse sk-translex.v2.norm.feats07.w2v.trainonpred.udpipe sk-ud-predPoS-test.conllu A slightly better after-deadline model (sk-translex.v2.norm.Case-feats07.w2v.trainonpred.udpipe), which we mention in the accompanying paper, is also included. It is applied in the same way (udpipe --tag --parse sk-translex.v2.norm.Case-feats07.w2v.trainonpred.udpipe sk-ud-predPoS-test.conllu). HR -- prune the Features to keep only Case and parse with the model: python3 feats2FEAT.py Case < hr-ud-predPoS-test.conllu \| udpipe --parse hr-translex.v2.norm.Case.w2v.trainonpred.udpipe NO -- put the UPOS annotation aside, tag Features with the model, merge with the left-aside UPOS annotation, and parse with the model (this hassle is because UDPipe cannot be told to keep UPOS and only change Features): cut -f1-4 no-ud-predPoS-test.conllu > tmp udpipe --tag no-translex.v2.norm.tgttagupos.srctagfeats.Case.w2v.udpipe no-ud-predPoS-test.conllu \| cut -f5- \| paste tmp - \| sed 's/^\t$//' \| udpipe --parse no-translex.v2.norm.tgttagupos.srctagfeats.Case.w2v.udpipe
dc.language.iso	slk
dc.language.iso	hrv
dc.language.iso	nor
dc.publisher	Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
dc.relation	info:eu-repo/grantAgreement/EC/H2020/644402
dc.relation.isreferencedby	http://web.science.mq.edu.au/~smalmasi/vardial4/pdf/VarDial26.pdf
dc.rights	Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subject	parsing
dc.subject	dependency parser
dc.subject	cross-lingual parsing
dc.subject	universal dependencies
dc.title	Slavic Forest, Norwegian Wood (models)
dc.type	toolService
metashare.ResourceInfo#ResourceComponentType#ToolServiceInfo.languageDependent	true
metashare.ResourceInfo#ContentInfo.detailedType	other
dc.rights.label	PUB
has.files	yes
branding	LINDAT / CLARIAH-CZ
contact.person	Rudolf Rosa rosa@ufal.mff.cuni.cz Charles University, UFAL
sponsor	European Union EC/H2020/644402 HimL - Health in my Language euFunds info:eu-repo/grantAgreement/EC/H2020/644402
sponsor	Univerzita Karlova (mimo GAUK) SVV 260 333 Specifický vysokoškolský výzkum nationalFunds
sponsor	Grantová agentura České republiky 15-10472S Morphologically and Syntactically Annotated Corpora of Many Languages nationalFunds
sponsor	Ministerstvo školství, mládeže a tělovýchovy České republiky LM2015071 LINDAT/CLARIN: Institut pro analýzu, zpracování a distribuci lingvistických dat nationalFunds
sponsor	Grantová agentura Univerzity Karlovy v Praze GAUK 15723/2014 Modelování závislostní syntaxe napříč jazyky nationalFunds
files.size	211839718
files.count	5