cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57771/be1g-vm57
title: MIC21 image dataset
title: MIC21 dataset

description: <p>The <strong>Multilingual Image Corpus</strong> provides fully annotated objects within images with segmentation masks, classified according to an Ontology of Visual Objects, thus offering data to train models specialised in object detection, segmentation and classification. </p><p>The Ontology of visual objects allows easy integration of annotated images in different datasets as well as learning the associations between objects in images. </p><p>The Ontology classes are translated into 25 languages and supplied with definitions and usage examples. The explicit association of objects and images with appropriate text fragments is relevant for multilingual image caption generation, image-to-text alignment and automatic question answering for images and video. </p>
DOI: 10.57771/hxe0-4826
title: MIC21 ontology of visual objects

description: The Ontology contains classes (706 representing visual objects and 147 representing their hypernyms), relations and axioms. Classes correspond (but are not limited) to WordNet concepts which can be represented by visual objects. Part of the relations and their properties are also inherited from WordNet. Axioms serve to model statements that are always true. A separate resource is available with the translations of the classes into 25 languages. 
		The Ontology of visual objects allows easy integration of annotated images in different datasets as well as learning the associations between objects in images and can be used for tasks such as multilingual image caption generation, image-to-text alignment and automatic question answering for images and video. 
		The ontology has been used for the annotation of the MIC21 Multilingual image corpus. <p></p>
DOI: 10.57771/cxef-da91
title: Multi-Language Vocabulary Evaluation Data Set
title: MuLVE

description: <p>Multi-Language Vocabulary Evaluation Data Set (MuLVE) is a data set consisting of vocabulary cards and real-life user answers, labeled whether the user answer is correct or incorrect. The data's source is user learning data from the Phase6 vocabulary trainer. The data set contains vocabulary questions in German and English, Spanish, and French as target language and is available in four different variations regarding pre-processing and deduplication.</p><p> </p><p>It is split up into four tab-separated files, one for each variation, per train and test set. The files include the following columns:</p><ul><li>cardId - numeric card ID</li><li>question - vocabulary card question</li><li>answer - vocabulary card answer</li><li>userAnswer - answer the user input</li><li>Label - True if user answer is correct, False if not</li><li>language - target language (English, French or Spanish)</li></ul><p>The processed data set variations do not include the include \textbf{userAnswer} columns but the following additional columns:</p><ul><li>question_norm - question normalized</li><li>answer_norm - answer normalized</li><li>userAnswer_norm - user answer normalized<br> </li></ul>
DOI: 10.57771/v36v-yb33
title: Multilingual translations of the MIC21 ontology classes

description: The classes of the MIC21 ontology of visual objects are translated into 25 languages (English, Albanian, Bulgarian, Basque, Catalan, Croatian, Danish, Dutch, Galician, German, Greek, Finnish, French, Icelandic, Italian, Lithuanian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Slovene, Spanish, and Swedish). Openly available wordnets have been used from the Extended Open Multilingual WordNet. For the Ontology classes which are not inherited from WordNet the appropriate WordNet hypernyms are taken. Where WordNet translations are not available, some additional sources of translations as BabelNet are employed. The Multilingual translations of classes are presented in a separate JSON file which contains information about the language and the translation source (sample). The translations of the Ontology classes are accompanied by their synonyms, the concept definition and usage examples (if available in the sources). The explicit association of objects and images with appropriate text fragments is relevant for multilingual image caption generation, image-to-text alignment and automatic question answering for images and video.
DOI: 10.57771/q901-7210
title: Nepali Monolingual written corpus
title: Corpus écrit monolingue népalais

description: The Nepali Monolingual written corpus is one of the 3 resources that constitute the Nepali National Corpus. The Nepali National Corpus was produced in 2006 in the framework of the project Bhasha Sanchar (“language communication”), also known as Nelralec, for Nepali Language Resources and Localization for Education and Communication; funded by the EU Asia IT&C programme, reference number ASIE/2004/091-777.<p><p>The Nepali Monolingual written corpus comprises the core corpus (core sample) and the general corpus. <p><p>The core sample (CS) represents the collection of Nepali written texts from 15 different genres with 2000 words each published between 1990 and 1992. It is based on FLOB/FROWN corpora and contains 802,000 words. <p><p>The general corpus (GC) consists of written texts collected opportunistically from a wide range of sources such as the internet webs, newspapers, books, publishers and authors. It contains 1,400,000 words. This part of the corpus was intended to allow corpus analyses that depend on a very large corpus.<p><p>The written corpus is morphogically-annotated. A part-of-speech (POS) tagset has been produced within the project: the Nelralec Tagset. This is a categorisation system for the manual and automated analysis of morphosyntactic units in Nepali.
description: Le corpus écrit monolingue népalais est l’une des 3 ressources qui composent le Corpus National Népalais. Le Corpus National Népalais a été produit en 2006 dans le cadre du projet Bhasha Sanchar (“communication langagière”), également connu sous le nom de Nelralec (Ressources linguistiques népalaises et localisation pour l’éducation et la communication); il a été financé par le programme de l’Union Européenne Asia IT&C, sous la référence ASIE/2004/091-777.

Le corpus écrit monolingue népalais est constitué du corpus fondamental (avec des échantillons centraux) et du corpus général. 

Le corpus fondamental représente la collection de texte écrit népalais de 15 genres différents contenant 2000 mots par genre, publiés entre 1990 et 1992. Il est basé sur les corpus FLOB/FROWN et contient 802 000 mots. 

Le corpus général comprend des textes écrits collectés de façon opportuniste à partir d’un large panel de sources tels que sites web, journaux, livres, éditeurs et auteurs. Il contient 1 400 000 mots. Cette partie du corpus a pour but de permettre les travaux d’analyse de corpus qui dépendent de corpus de très grande taille.

Le corpus écrit est annoté au niveau morphologique. Un jeu d’étiquettes pour la partie du discours a été produit dans le projet : le jeu d’étiquettes Nelralec. C’est un système de catégorisation pour l’analyse manuelle et automatisée des unités morphosyntaxiques en népalais.
DOI: 10.6073/pasta/81aadb31fe08adad85dbc1f02d2fbebc
title: Jornada Basin LTER: Wireless meteorological station at NPP G-IBPE site: 1-hour summary data: 2013 - ongoing

description: Hourly summary data at NPP G-IBPE met station. Average/maximum/minimum air temperature; average relative humidity and wind direction; average/maximum wind speed. These are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP G-IBPE site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.57771/8cd8-jg82
title: NLP4FUN Dataset
title: NLP4FUN

description: The NLP4FUN dataset contains 420 instances of the language game La Ghigliottina (“The Guillotine”), the final game of an Italian TV show called L’eredità. An instance of the game consists of a set of 5 clue words that are all semantically related to a sixth word (that constitutes the solution for that instance).<p>The dataset has been used in the context of the NLP4FUN task (https://nlp4fun.github.io/) during the EVALITA 2018 evaluation campaign  (http://www.evalita.it/2018). It is divided into a training set for the system development (315 instances), and a test set for the evaluation (105 instances).
DOI: 10.57771/dp3s-k858
title: NPChunks
title: NPChunks

description: NPChunks is a training corpus containing approximately 1,000 sentences, with a total of 24,243 tokens, selected randomly from the written part of the CINTIL corpus. For more information on the CINTIL corpus, see ELRA-W0050, ISLRN: 176-775-844-396-0.<p><p>The corpus is PoS-annotated at token level, including punctuation. Noun Phrases were recognized and annotated with specific tags. It was automatically PoS-tagged with MBT tagger (http://ilk.uvt.nl/mbt/), and lemmatized with MBLEM (http://ilk.uvt.nl/mbma/), following the annotation scheme of the Corpus of Reference of Contemporary Portuguese. YamCha software (http://chasen.org/~taku/software/yamcha/) was used to recognize chunks that consist of Noun Phrases and to identify the elements appearing at the beginning, in the middle and at the end of a noun phrase.
description: NPChunks est un corpus d’entraînement comprenant environ 1,000 phrases, avec un total de 24,243 mots, choisis de manière aléatoire dans la partie écrite du corpus CINTIL. Pour plus d’informations sur le corpus CINTIL, voir ELRA-W0050, ISLRN: 176-775-844-396-0.

Le corpus a été annoté en parties du discours (signes de ponctuation inclus). Les syntagmes nominaux ont été identifiés et annotés avec des étiquettes spécifiques. Le corpus a été annoté automatiquement en parties du discours avec l’étiqueteur MBT (http://ilk.uvt.nl/mbt/), et lemmatisé  avec MBLEM (http://ilk.uvt.nl/mbma/), selon le schéma d’annotation du Corpus de Référence du Portugais Contemporain. Le software YamCha (http://chasen.org/~taku/software/yamcha/) a été utilisé pour identifier les syntagmes nominaux ainsi que les éléments apparaissant au début, au milieu et à la fin du syntagme.
DOI: 10.57771/v55q-6794
title: PANACEA Environment English monolingual corpus
title: Corpus monolingue anglais PANACEA - domaine de l’environnement

description: The PANACEA Environment English monolingual corpus was acquired in the framework of the PANACEA project (Platform for Automatic, Normalized Annotation and Cost-Effective Acquisition of Language Resources for Human Language Technologies), under the European Commission's Seventh Framework Programme. <p><p>This corpus contains documents that were acquired from the web, were automatically detected to be in the English language and were automatically classified as relevant to the “Environment” domain. It was constructed in the summer of 2011 using the Focused Monolingual Crawler (FMC) developed in the context of PANACEA.<p><p>The corpus contains 50,541,538 tokens, excluding tokens in a) short (smaller than 10 tokens) paragraphs, b) paragraphs that were automatically classified as boilerplate and c) paragraphs that were automatically detected in a language other than English. They are divided into a total of 28,071 documents that were crawled from 3,121 web sites. The dataset consists of the original crawled HTML files and the corresponding CesDoc XML files with basic metadata.
description: Le corpus monolingue anglais PANACEA - domaine de l’environnement a été acquis dans le cadre du projet PANACEA (Platform for Automatic, Normalized Annotation and Cost-Effective Acquisition of Language Resources for Human Language Technologies), du septième programme-cadre de la Commission européenne. 

Ce corpus comprend des documents acquis depuis le web, qui ont été détectés automatiquement comme étant de langue anglaise et classés automatiquement comme appartenant au domaine de l’environnement. Il a été construit en été 2011 au moyen du FMC (Focused Monolingual Crawler), développé dans le contexte de PANACEA. 

Le corpus contient 50 541 538 tokens, en excluant les tokens se trouvant a) dans les paragraphes courts (moins de 10 tokens), b) dans les paragraphes qui ont été classés automatiquement comme « boilerplate » et c) dans les paragraphes qui ont été détectés automatiquement comme étant dans une autre langue que l’anglais. Les tokens proviennent d’un total de 28 071 documents qui ont été crawlés depuis 3 121 sites web. L’ensemble de données comprend les fichiers HTML d’origine crawlés et les fichiers XML CesDoc correspondants avec les métadonnées de base.
DOI: 10.57771/qq72-mg42
title: PANACEA Environment French monolingual corpus
title: Corpus monolingue français PANACEA - domaine de l’environnement

description: The PANACEA Environment French monolingual corpus was acquired in the framework of the PANACEA project (Platform for Automatic, Normalized Annotation and Cost-Effective Acquisition of Language Resources for Human Language Technologies), under the European Commission's Seventh Framework Programme. <p><p>This corpus contains documents that were acquired from the web, were automatically detected to be in the French language and were automatically classified as relevant to the “Environment” domain. It was constructed in the summer of 2011 using the Focused Monolingual Crawler (FMC) developed in the context of PANACEA.<p><p>The corpus contains 47,364,125 tokens, excluding tokens in a) short (smaller than 10 tokens) paragraphs, b) paragraphs that were automatically classified as boilerplate and c) paragraphs that were automatically detected in a language other than French. They are divided into a total of 23,514 documents that were crawled from 1,969 web sites. The dataset consists of the original crawled HTML files and the corresponding CesDoc XML files with basic metadata.
description: Le corpus monolingue français PANACEA - domaine de l’environnement a été acquis dans le cadre du projet PANACEA (Platform for Automatic, Normalized Annotation and Cost-Effective Acquisition of Language Resources for Human Language Technologies), du septième programme-cadre de la Commission européenne. 

Ce corpus comprend des documents acquis depuis le web, qui ont été détectés automatiquement comme étant de langue française et classés automatiquement comme appartenant au domaine de l’environnement. Il a été construit en été 2011 au moyen du FMC (Focused Monolingual Crawler), développé dans le contexte de PANACEA. 

Le corpus contient 47 364 125 tokens, en excluant les tokens se trouvant a) dans les paragraphes courts (moins de 10 tokens), b) dans les paragraphes qui ont été classés automatiquement comme « boilerplate » et c) dans les paragraphes qui ont été détectés automatiquement comme étant dans une autre langue que le français. Les tokens proviennent d’un total de 23 514 documents qui ont été crawlés depuis 1 969 sites web. L’ensemble de données comprend les fichiers HTML d’origine crawlés et les fichiers XML CesDoc correspondants avec les métadonnées de base.
DOI: 10.57771/9p08-4d74
title: PANACEA Environment Greek monolingual corpus
title: Corpus monolingue grec PANACEA - domaine de l’environnement

description: The PANACEA Environment Greek monolingual corpus was acquired in the framework of the PANACEA project (Platform for Automatic, Normalized Annotation and Cost-Effective Acquisition of Language Resources for Human Language Technologies), under the European Commission's Seventh Framework Programme. <p><p>This corpus contains documents that were acquired from the web, were automatically detected to be in the Greek language and were automatically classified as relevant to the “Environment” domain. It was constructed in the summer of 2011 using the Focused Monolingual Crawler (FMC) developed in the context of PANACEA.<p><p>The corpus contains 27,958,530 tokens, excluding tokens in a) short (smaller than 10 tokens) paragraphs, b) paragraphs that were automatically classified as boilerplate and c) paragraphs that were automatically detected in a language other than Greek. They are divided into a total of 16,073 documents that were crawled from 1,063 web sites. The dataset consists of the original crawled HTML files and the corresponding CesDoc XML files with basic metadata.
description: Le corpus monolingue grec PANACEA - domaine de l’environnement a été acquis dans le cadre du projet PANACEA (Platform for Automatic, Normalized Annotation and Cost-Effective Acquisition of Language Resources for Human Language Technologies), du septième programme-cadre de la Commission européenne. 

Ce corpus comprend des documents acquis depuis le web, qui ont été détectés automatiquement comme étant de langue grecque et classés automatiquement comme appartenant au domaine de l’environnement. Il a été construit en été 2011 au moyen du FMC (Focused Monolingual Crawler), développé dans le contexte de PANACEA. 

Le corpus contient 27 958 530 tokens, en excluant les tokens se trouvant a) dans les paragraphes courts (moins de 10 tokens), b) dans les paragraphes qui ont été classés automatiquement comme « boilerplate » et c) dans les paragraphes qui ont été détectés automatiquement comme étant dans une autre langue que le grec. Les tokens proviennent d’un total de 16 073 documents qui ont été crawlés depuis 1 063 sites web. L’ensemble de données comprend les fichiers HTML d’origine crawlés et les fichiers XML CesDoc correspondants avec les métadonnées de base.
DOI: 10.57771/0ee2-ta80
title: PANACEA Environment Italian monolingual corpus
title: Corpus monolingue italien PANACEA - domaine de l’environnement

description: The PANACEA Environment Italian monolingual corpus was acquired in the framework of the PANACEA project (Platform for Automatic, Normalized Annotation and Cost-Effective Acquisition of Language Resources for Human Language Technologies), under the European Commission's Seventh Framework Programme. <p><p>This corpus contains documents that were acquired from the web, were automatically detected to be in the Italian language and were automatically classified as relevant to the “Environment” domain. It was constructed in the summer of 2011 using the Focused Monolingual Crawler (FMC) developed in the context of PANACEA.<p><p>The corpus contains 40,044,852 tokens, excluding tokens in a) short (smaller than 10 tokens) paragraphs, b) paragraphs that were automatically classified as boilerplate and c) paragraphs that were automatically detected in a language other than Italian. They are divided into a total of 16,159 documents that were crawled from 1,211 web sites. The dataset consists of the original crawled HTML files and the corresponding CesDoc XML files with basic metadata.
description: Le corpus monolingue italien PANACEA - domaine de l’environnement a été acquis dans le cadre du projet PANACEA (Platform for Automatic, Normalized Annotation and Cost-Effective Acquisition of Language Resources for Human Language Technologies), du septième programme-cadre de la Commission européenne. 

Ce corpus comprend des documents acquis depuis le web, qui ont été détectés automatiquement comme étant de langue italienne et classés automatiquement comme appartenant au domaine de l’environnement. Il a été construit en été 2011 au moyen du FMC (Focused Monolingual Crawler), développé dans le contexte de PANACEA. 

Le corpus contient 40 044 852 tokens, en excluant les tokens se trouvant a) dans les paragraphes courts (moins de 10 tokens), b) dans les paragraphes qui ont été classés automatiquement comme « boilerplate » et c) dans les paragraphes qui ont été détectés automatiquement comme étant dans une autre langue que l’italien. Les tokens proviennent d’un total de 16 159 documents qui ont été crawlés depuis 1 211 sites web. L’ensemble de données comprend les fichiers HTML d’origine crawlés et les fichiers XML CesDoc correspondants avec les métadonnées de base.
DOI: 10.57771/a4g2-yt93
title: PANACEA Environment Spanish monolingual corpus
title: Corpus monolingue espagnol PANACEA - domaine de l’environnement

description: The PANACEA Environment Spanish monolingual corpus was acquired in the framework of the PANACEA project (Platform for Automatic, Normalized Annotation and Cost-Effective Acquisition of Language Resources for Human Language Technologies), under the European Commission's Seventh Framework Programme. <p><p>This corpus contains documents that were acquired from the web, were automatically detected to be in the Spanish language and were automatically classified as relevant to the “Environment” domain. It was constructed in the summer of 2011 using the Focused Monolingual Crawler (FMC) developed in the context of PANACEA.<p><p>The corpus contains 46,225,624 tokens, excluding tokens in a) short (smaller than 10 tokens) paragraphs, b) paragraphs that were automatically classified as boilerplate and c) paragraphs that were automatically detected in a language other than Spanish. They are divided into a total of 26,009 documents that were crawled from 2,053 web sites. The dataset consists of the original crawled HTML files and the corresponding CesDoc XML files with basic metadata.
description: Le corpus monolingue espagnol PANACEA - domaine de l’environnement a été acquis dans le cadre du projet PANACEA (Platform for Automatic, Normalized Annotation and Cost-Effective Acquisition of Language Resources for Human Language Technologies), du septième programme-cadre de la Commission européenne. 

Ce corpus comprend des documents acquis depuis le web, qui ont été détectés automatiquement comme étant de langue espagnole et classés automatiquement comme appartenant au domaine de l’environnement. Il a été construit en été 2011 au moyen du FMC (Focused Monolingual Crawler), développé dans le contexte de PANACEA. 

Le corpus contient 46 225 624 tokens, en excluant les tokens se trouvant a) dans les paragraphes courts (moins de 10 tokens), b) dans les paragraphes qui ont été classés automatiquement comme « boilerplate » et c) dans les paragraphes qui ont été détectés automatiquement comme étant dans une autre langue que l’espagnol. Les tokens proviennent d’un total de 26 009 documents qui ont été crawlés depuis 2 053 sites web. L’ensemble de données comprend les fichiers HTML d’origine crawlés et les fichiers XML CesDoc correspondants avec les métadonnées de base.