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  • GreynirPackage (2021-05-12)

    GreynirPackage is a Python 3 package for working with Icelandic natural language text. Greynir can parse text into sentence trees, find lemmas, inflect noun phrases, assign part-of-speech tags and much more. Greynir's sentence trees can inter alia be used to extract information from text, for instance about people, titles, entities, facts, actions and opinions. Greynir uses the Tokenizer package, by the same authors, to tokenize text. More information at https://github.com/mideind/GreynirPackage and detailed documentation at https://greynir.is/doc/. GreynirPackage er Python 3 pakki sem vinnur með íslenskan texta. Greynir þáttar texta í setningar, lemmar og markar texta, beygir nafnliði og margt fleira. Hægt er að nýta þáttunartrén sem tólið býr til í þeim tilgangi að draga upplýsingar út úr texta, til dæmis um manneskjur, starfstitla, sérnafnaeiningar, staðreyndir, atburði og skoðanir. Greynir notar Tokenizer-pakkann, eftir sömu höfunda, til að tilreiða texta. Frekari upplýsingar má finna á https://github.com/mideind/GreynirPackage og ítarlega skjölun (á ensku) á https://greynir.is/doc/.

  • COMBO-based UD Parser for Icelandic 22.12

    ENGLISH: This Universal Dependencies parser for Icelandic was trained with COMBO [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 [4]. Its UAS (unlabeled attachment score) is 88.80 (89.00 on a pre-tokenized text file) and its LAS (labeled attachment score) is 85.52 (85.71 if pre-tokenized).   ICELANDIC: Þessi UD-þáttari var þjálfaður með COMBO [1]. Hann var þjálfaður 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 88.80 (89.00 á fortókuðu skjali) á UAS (unlabeled attachment score) og 85.52 (85.71 á fortókuðu skjali) á LAS (labeled attachment score). [1] COMBO: https://gitlab.clarin-pl.eu/syntactic-tools/combo/  [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

  • The Scottish Gaelic Linguistic Toolkit

    A linguistic analyser for tagging, lemmatisation and parsing of Scottish Gaelic texts. Morphological and syntactic analyses are available directly from the webpage (through the text area window) or as a web service. A simple tagger option using a restricted tagset is also provided. LANGUAGE DATA The tagger was trained with the ARCOSG corpus (https://github.com/Gaelic-Algorithmic-Research-Group/ARCOSG) using Conditional Random Fields with scikit-learn (https://scikit-learn.org). The lemmatiser was build on the top of a lexicon provided by Michael Bauer and Will Robertson (www.faclair.com). The integrated UDPipe parser (http://ufal.mff.cuni.cz/udpipe) was trained with link2 option on Colin Batchelor's UD Gaelic Treebank (https://universaldependencies.org/). OUTPUT FORMAT Vertical tabular: - simple tabbed text for direct html page results, - simple tabbed text file or conllu file for web service results. Grammatical information encoded through ARCOSG tagset and UD tagset. EVALUATION Full tagger accuracy of 90.7% (measured on about 4.6% of the ARCOSG corpus) Simple tagger accuracy of 94.7% (measured on about 4.6% of the ARCOSG corpus) Lemmatisation and Parsing not evaluated yet.

  • BinPackage 0.4.4 (22.10)

    BinPackage is a Python Package that embeds the vocabulary of the DMII (https://bin.arnastofnun.is) and offers various lookups and queries of the data. The database, maintained by The Árni Magnússon Institute for Icelandic Studies, contains over 6.5 million entries, over 3.1 million unique word forms, and about 300,000 distinct lemmas. The database has been encapsulated in an easy-to-install Python package, and compressed from 400+ megabyte CSV file to an ~80 megabyte indexed binary structure. More information at: https://github.com/mideind/BinPackage BinPackage er Python-pakki utan um BÍN, Beygingarlýsingu íslensks nútímamáls (https://bin.arnastofnun.is), sem inniheldur yfir 6,5 milljónir færslna, 3,1 milljón einstakra orðmynda og um 300.000 stakar lemmur. Stofnun Árna Magnússonar í íslenskum fræðum heldur utan um gagnagrunninn. Gagnagrunninum, um 400 megabæta CSV-skrá, hefur verið pakkað í um 80 megabæta tvíundarbyggingu með vísum. Frekari upplýsingar á: https://github.com/mideind/BinPackage

  • The Database of Lithuanian multiword expressions

    The Database of Lithuanian multiword expressions (MWEs) is freely accessible for online search at: https://resursai.pastovu.vdu.lt/paieska/paprastoji from 2019. It contains two-word and three-word MWEs extracted from the DELFI.lt corpus representing news texts on the various topics (https://klc.vdu.lt/pastovuSearch.html). First, 12,000 MWEs (mostly collocations, a few idioms) were included in the database. In 2022, the database was updated adding new collocations from the same corpus and filtering arbitrary collocations: out of appr. 19,000 collocations appr. 9000 are marked as arbitrary collocations, i.e., having lexical collocability restrictions. The database provides rich information about the usage of collocations: lemma, word forms, frequencies (in the DELFI.lt corpus), morphological information, syntactic relations, grammatical variants, text genres, and usage examples. Usage variation cases are also illustrated, for example, word order changes or insertions between collocation constituents.

  • ABLTagger (Lemmatizer) - 3.1.0

    A neural Lemmatizer for Icelandic. In this submission, you will find a pretrained lemmatizer model for ABLTagger v3.1.0. In this submission we provide a small lemmatizer that accepts as input the tokens and tags from the revised tagset. The lemmatizer achieves an accuracy of 98.3% on MIM-Gold (21.05, cross-validation). Það er minni nákvæmni en Nefnir. For installation, usage, and other instructions see https://github.com/icelandic-lt/POS. You should also check if a newer version is out (see README.md - versions) on CLARIN: - Model files ------------------------------------------------------------------------------------------- Lemmari fyrir íslensku. Í þessum pakka er forþjálfað lemmunar líkan fyrir ABLTagger v3.1.0. Í þessari útgáfu er lítill lemmari sem tekur inn tóka og mörk úr nýja markamengið. Lemmarinn nær 98.3% nákvæmni á MÍM-Gull (21.05, krossprófanir). Það er minni nákvæmni en Nefnir. Fyrir uppsetningar-, notenda- og aðrar leiðbeiningar sjá https://github.com/icelandic-lt/POS. Einnig er gott að athuga þar hvort ný útgáfa sé komin út (sjá README.md - versions) Á CLARIN: - Gögn fyrir líkan

  • The Orange workflow for observing collocation trends ColTrend 1.0

    The Orange workflow for observing collocation trends ColTrend 1.0 ColTrend is a workflow (.OWS file) for Orange Data Mining (an open-source machine learning and data visualization software: https://orangedatamining.com/) that allows the user to observe temporal collocation trends in corpora. The workflow consists of a series of Python scripts, data filters, and visualizers. As input, the workflow takes a .CSV file with data on collocations and their relative frequencies by year of publication extracted from a corpus. As output, it provides a .TSV file containing the same data (or a filtered selection thereof) enriched with four measures that indicate the collocation’s temporal trend in the corpus: (1) the slope (k) of a linear regression model fitted to the frequency data, which indicates whether the frequency of use of the collocation is increasing or declining; (2) the coefficient of determination (R2) of the linear regression model, indicating how linear the change in the collocation’s use is; (3) the ratio (m) of maximum relative frequency and average relative frequency, which indicates peaks in collocation usage; and (4) the coefficient of recent growth (t), which indicates an increased usage of the collocation in the last three years of the observed corpus data. The entry also contains three .CSV files that can be used to test the workflow. The files contain collocation candidates (along with their relative frequencies per year of publication) extracted from the Gigafida 2.0 Corpus of Written Slovene (https://viri.cjvt.si/gigafida/) with three different syntactic structures (as defined in http://hdl.handle.net/11356/1415): 1) p0-s0 (adjective + noun, e.g. rezervni sklad), 2) s0-s2 (noun + noun in the genitive case, e.g. ukinitev lastnine), and 3) gg-s4 (verb + noun in the accusative case, e.g. pripraviti besedilo). It should be noted that only collocation candidates with absolute frequency of 15 and above were extracted. Please note that the ColTrend workflow requires the installation of the Text Mining add-on for Orange. For installation instructions as well as a more detailed description of the different phases of the workflow and the measures used to observe the collocation trends, please consult the README file.

  • GreynirCorrect (1.0.2)

    GreynirCorrect is a Python 3 package and a command line tool for checking and correcting various types of spelling and grammar errors in Icelandic text. GreynirCorrect relies on the Tokenizer package, by the same authors, to tokenize text. More information can be found at https://github.com/mideind/GreynirCorrect, and detailed documentation at https://yfirlestur.is/doc/. GreynirCorrect er Python 3 pakki og skipanalínutól sem bendir á og leiðréttir ýmsar tegundir stafsetningar- og málvillna í íslenskum texta. GreynirCorrect reiðir sig á Tokenizer-pakkann, eftir sömu höfunda, til að tilreiða textann. Frekari upplýsingar má finna á https://github.com/mideind/GreynirCorrect, og ítarlega skjölun (á ensku) á https://yfirlestur.is/doc/.

  • GreynirCorrect (1.0.0)

    GreynirCorrect GreynirCorrect is a Python package and a command line tool for checking and correcting context-independent spelling errors in Icelandic text. GreynirCorrect relies on the Tokenizer package, by the same authors, to tokenize text. More information at: https://github.com/mideind/GreynirCorrect GreynirCorrect er Python-pakki og skipanalínutól sem leiðréttir ósamhengisháðar ritvillur í íslenskum texta. GreynirCorrect reiðir sig á Tokenizer-pakkann, eftir sömu höfunda, til að tilreiða textann. Frekari upplýsingar á: https://github.com/mideind/