Comprehensive Arabic LEMmas is a lexicon covering a large list of Arabic lemmas and their corresponding inflected word forms (stems) with details (POS + Root). Each lexical entry represents a lemma followed by all its possible stems and each stem is enriched by its morphological features especially the root and the POS.
It is composed of 164,845 lemmas representing 7,200,918 stems, detailed as follow:
757 Arabic particles
2,464,631 verbal stems
4,735,587 nominal stems
The lexicon is provided as an LMF conformant XML-based file in UTF8 encoding, which represents about 1,22 Gb of data.
Citation:
– Namly Driss, Karim Bouzoubaa, Abdelhamid El Jihad, and Si Lhoussain Aouragh. “Improving Arabic Lemmatization Through a Lemmas Database and a Machine-Learning Technique.” In Recent Advances in NLP: The Case of Arabic Language, pp. 81-100. Springer, Cham, 2020.
This corpus was originally created for performance testing (server infrastructure CorpusExplorer - see: diskurslinguistik.net / diskursmonitor.de). It includes the filtered database (German texts only) of CommonCrawl (as of March 2018). First, the URLs were filtered according to their top-level domain (de, at, ch). Then the texts were classified using NTextCat and only uniquely German texts were included in the corpus. The texts were then annotated using TreeTagger (token, lemma, part-of-speech). 2.58 million documents - 232.87 million sentences - 3.021 billion tokens. You can use CorpusExplorer (http://hdl.handle.net/11234/1-2634) to convert this data into various other corpus formats (XML, JSON, Weblicht, TXM and many more).
Relationship extraction models for the Czech language. Models are trained on CERED (dataset created by distant supervision on Czech Wikipedia and Wikidata) and recognize a subset of Wikidata relations (listed in CEREDx.LABELS).
We supply a demo.py that performs inference on user-defined input and requirements.txt file for pip. Adapt the demo code to use the model.
Both the dataset and the models are presented in Relationship Extraction thesis.
Transcripts of longitudinal audio recordings of 7 Czech typical monolingual children between 1;7 to 3;9. Files are in plain text with UTF-8 encoding. Each file represents one recording session of one of the target children and is named with the presudonym of the child and her age at the given session in form YMMDD. Transcription rules and other details are to find on the homepage coczefla.ff.cuni.cz.
A new version of the previously published corpus Chroma. The version 2023.04 includes six children. Two transcripts (Julie20221, Klara30424) were removed since they did not meet the criteria on the dialogical format. The transcripts were revised (eliminating typing errors and inconsistencies in the transcription format) and morphologically annotated by the automatic tool MorphoDiTa. Detailed manual control of the annotation was performed on children's utterances; the annotation of adult data was not checked yet. Files are in plain text with UTF-8 encoding. Each file represents one recording session of one of the target children and is named with the alias of the child and their age at the given session in form YMMDD. Transcription rules and other details can be found on the homepage coczefla.ff.cuni.cz.
A new version of the previously published corpus Chroma wih morphological annotation. The version 2023.07 differs from 2023.04 in that it includes all seven children and it went through an additional careful check of consistency and conformity to the CHAT transcription principles.
Two transcripts (Julie20221, Klara30424) from the previous versions (2022.07, 2019.07) were removed since they did not meet our criteria on dialogical format. All transcripts of recordings made during one day were split into one file. Thus, version 2023.07 consists of 183 files/transcripts. The number of utterances and tokens given here in LINDAT corresponds to children's lines only.
Files are in plain text with UTF-8 encoding. Each file represents one recording session of one of the target children and is named with the alias of the child and their age at the given session in form YMMDD. Transcription rules and other details can be found on the homepage coczefla.ff.cuni.cz.
Czech data - both train and test+eval sets, as well as the valency dictionary - for the CoNLL 2009 Shared Task. Documentation is included. The data are generated from PDT 2.0. LDC catalog number: LDC2009E34B and MSM 0021620838 (http://ufal.mff.cuni.cz:8080/bib/?section=grant&id=116488695895567&mode=view)
Czech trial (example) data for CoNLL 2009 Shared Task. The data are generated from PDT 2.0. LDC2009E32B and MSM 0021620838 (http://ufal.mff.cuni.cz:8080/bib/?section=grant&id=116488695895567&mode=view)
CoNLL 2017 and 2018 shared tasks:
Multilingual Parsing from Raw Text to Universal Dependencies
This package contains the test data in the form in which they ware presented
to the participating systems: raw text files and files preprocessed by UDPipe.
The metadata.json files contain lists of files to process and to output;
README files in the respective folders describe the syntax of metadata.json.
For full training, development and gold standard test data, see
Universal Dependencies 2.0 (CoNLL 2017)
Universal Dependencies 2.2 (CoNLL 2018)
See the download links at http://universaldependencies.org/.
For more information on the shared tasks, see
http://universaldependencies.org/conll17/
http://universaldependencies.org/conll18/
Contents:
conll17-ud-test-2017-05-09 ... CoNLL 2017 test data
conll18-ud-test-2018-05-06 ... CoNLL 2018 test data
conll18-ud-test-2018-05-06-for-conll17 ... CoNLL 2018 test data with metadata
and filenames modified so that it is digestible by the 2017 systems.