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  • Slavic Forest, Norwegian Wood (models)

    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

  • Terminal-based CoNLL-file viewer, v2

    A simple way of browsing CoNLL format files in your terminal. Fast and text-based. To open a CoNLL file, simply run: ./view_conll sample.conll The output is piped through less, so you can use less commands to navigate the file; by default the less searches for sentence beginnings, so you can use "n" to go to next sentence and "N" to go to previous sentence. Close by "q". Trees with a high number of non-projective edges may be difficult to read, as I have not found a good way of displaying them intelligibly. If you are on Windows and don't have less (but have Python), run like this: python view_conll.py sample.conll For complete instructions, see the README file. You need Python 2 to run the viewer.

  • Service for querying dependency treebanks Drevesnik 1.0

    Drevesnik (https://orodja.cjvt.si/drevesnik/) is an online service for querying syntactically parsed corpora in Slovenian using the Universal Dependencies annotation scheme with easy-to-use query language on the one hand and user-friendly graph visualizations on the other. It is based on the open-source dep_search tool (https://github.com/TurkuNLP/dep_search), which was localized and modified so as to also support querying by JOS morphosyntactic tags, random distribution of results, and filtering by sentence length. The source code and the documentation for the search backend and the web user interface are publicly available on the CLARIN.SI GitHub repository https://github.com/clarinsi/drevesnik. This submission corresponds to release 1.0: https://github.com/clarinsi/drevesnik/releases/tag/1.0.

  • Biaffine-based UD Parser for Icelandic 22.12

    ENGLISH: This Universal Dependencies parser for Icelandic was trained with Diaparser [1]. This version of it was trained on v2.11 of UD_Icelandic-IcePaHC [2] and UD_Icelandic-Modern [3]. (Note that texts in UD_Icelandic-Modern [3] labeled RUV_TGS_2017 and RUV_ESP_2017 were not included here as these were originally parsed with COMBO-based UD Parser 22.10 [4] and the output subsequently corrected.) The parser utilizes information from an ELECTRA language model [5]. Its UAS (unlabeled attachment score) is 89.58 and its LAS (labeled attachment score) is 86.46.   ICELANDIC: Þessi UD-þáttari var þjálfaður með Diaparser [1]. Þessi útgáfa hans var þjálfuð á útgáfu 2.11 af UD_Icelandic-IcePaHC [2] og UD_Icelandic-Modern [3]. (Ath. að textar í UD_Icelandic-Modern [3] merktir RUV_TGS_2017 og RUV_ESP_2017 voru ekki notaðir við þjálfunina þar sem þeir voru upphaflega þáttaðir með COMBO-based UD Parser 22.10 [4] og úttakið leiðrétt að því loknu.) Þáttarinn nýtir sér upplýsingar úr ELECTRA-mállíkani [5]. Hann skorar 89.58 á UAS (unlabeled attachment score) og 86.46 á LAS (labeled attachment score). [1] Diaparser: https://github.com/Unipisa/diaparser  [2] UD_Icelandic-IcePaHC: https://github.com/UniversalDependencies/UD_Icelandic-IcePaHC/  [3] UD_Icelandic-Modern: https://github.com/UniversalDependencies/UD_Icelandic-Modern/  [4] COMBO-based UD Parser 22.10: http://hdl.handle.net/20.500.12537/272 [5] electra-base-igc-is: https://huggingface.co/jonfd/electra-base-igc-is

  • Biaffine-based UD Parser 22.10

    ENGLISH: This Universal Dependencies parser for Icelandic was trained with Diaparser [1] on IcePaHC [2] and UD_Icelandic-Modern [3], the latter one having been revised before training, as some duplicate sentences had to be removed. The parser utilizes information from an ELECTRA language model [4]. Its UAS (unlabeled attachment score) is 89.52 and its LAS (labeled attachment score) is 86.23.

  • COMBO-based UD Parser 22.10

    ENGLISH: This Universal Dependencies parser for Icelandic was trained with COMBO on IcePaHC and UD_Icelandic-Modern, the latter one having been revised before training, as some duplicate sentences had to be removed. It utilizes information from an ELECTRA language model (https://huggingface.co/jonfd/electra-base-igc-is). Its UAS (unlabeled attachment score) is 89.13 and its LAS (labeled attachment score) is 85.97.

  • UDConverter 22.01

    UDConverter is a tool for converting constituency treebanks in the format of PPCHE (Penn Parsed Corpora of Historical English) to dependency treebanks following the Universal Dependencies framework. The tool is specifically configured to convert treebanks in the IcePaHC format. This version has an 81.39 LAS (labeled attachment score). UDConverter er tól til að varpa liðgerðartrjábönkum á sniði PPCHE (Penn Parsed Corpora of Historical English) yfir í venslatrjábanka samkvæmt Universal Dependencies-sniði. Tólið er sérstaklega þróað til að varpa trjábönkum á sniði IcePaHC. Þessi útgáfa er með 81,39 LAS (labeled attachment score).

  • Service for querying dependency treebanks Drevesnik 1.1

    Drevesnik (https://orodja.cjvt.si/drevesnik/) is an online service for querying Slovenian corpora parsed with the Universal Dependencies annotation scheme. It features an easy-to-use query language on the one hand and user-friendly graph visualizations on the other. It is based on the open-source dep_search tool (https://github.com/TurkuNLP/dep_search), which was localized and modified so as to also support querying by JOS morphosyntactic tags, random distribution of results, and filtering by sentence length. The source code and the documentation for the search backend and the web user interface are publicly available on the CLARIN.SI GitHub repository https://github.com/clarinsi/drevesnik. This submission corresponds to release 1.1: https://github.com/clarinsi/drevesnik/releases/tag/1.1, which brings improved architecture, documentation and branding in comparison to release 1.0.

  • Dependency tree extraction tool STARK 2.0

    STARK is a python-based command-line tool for extraction of dependency trees from parsed corpora, aimed at corpus-driven linguistic investigations of syntactic and lexical phenomena of various kinds. It takes a treebank in the CONLL-U format as input and returns a list of all relevant dependency trees with frequency information and other useful statistics, such as the strength of association between the nodes of a tree, or its significance in comparison to another treebank. For installation, execution and the description of various user-defined parameter settings, see the official project page at: https://github.com/clarinsi/STARK In comparison with v1, this version introduces several new features and improvements, such as the option to set parameters in the command line, compare treebanks or visualise results online.