AKCES-GEC is a grammar error correction corpus for Czech generated from a subset of AKCES. It contains train, dev and test files annotated in M2 format.
Note that in comparison to CZESL-GEC dataset, this dataset contains separated edits together with their type annotations in M2 format and also has two times more sentences.
If you use this dataset, please use following citation:
@article{naplava2019wnut,
title={Grammatical Error Correction in Low-Resource Scenarios},
author={N{\'a}plava, Jakub and Straka, Milan},
journal={arXiv preprint arXiv:1910.00353},
year={2019}
}
Description: This xml file is a lexicon containing all 21952 (28x28x28) Arabic triliteral combinations (roots). the file is split into three parts as follow: the first part contains the phonetic constraints that must be taken into account in the formation of Arabic roots (for more details see all_phonetic_rules.xml in http://arabic.emi.ac.ma/alelm/?q=Resources). the second part contains the lexicons that were used to create this lexicon (see in lexicons tag). the third part contains the roots.
ISLRN: 813-907-570-946-2
This improved version is an extension of the original Arabic Wordnet (http://globalwordnet.org/arabic-wordnet/awn-browser/), it was enriched by new verbs, nouns including the broken plurals that is a specific form for Arabic words.
An LMF conformant XML-based file containing a comprehensive Arabic broken plural list. The file contains 12,249 singular words with their corresponding BPs
A large web corpus (over 10 billion tokens) licensed under CreativeCommons license family in 50+ languages that has been extracted from CommonCrawl, the largest publicly available general Web crawl to date with about 2 billion crawled URLs.
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.