cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57771/wp3m-a585
title: PANACEA Labour Greek monolingual corpus
title: Corpus monolingue grec PANACEA - domaine de la législation du travail

description: The PANACEA Labour 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 “Labour Legislation” 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 21,077,196 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 7,124 documents that were crawled from 598 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 la législation du travail 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 la législation du travail. Il a été construit en été 2011 au moyen du FMC (Focused Monolingual Crawler), développé dans le contexte de PANACEA. 

Le corpus contient 21 077 196 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 7 124 documents qui ont été crawlés depuis 598 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/h05n-9z88
title: PANACEA Labour Italian monolingual corpus
title: Corpus monolingue italien PANACEA - domaine de la législation du travail

description: The PANACEA Labour 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 “Labour Legislation” 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 70,563,320 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 12,706 documents that were crawled from 864 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 la législation du travail 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 la législation du travail. Il a été construit en été 2011 au moyen du FMC (Focused Monolingual Crawler), développé dans le contexte de PANACEA. 

Le corpus contient 70 563 320 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 12 706 documents qui ont été crawlés depuis 864 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/rqw8-va41
title: PANACEA Labour Spanish monolingual corpus
title: Corpus monolingue espagnol PANACEA - domaine de la législation du travail

description: The PANACEA Labour 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 “Labour Legislation” 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 53,922,118 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 13,188 documents that were crawled from 1,015 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 la législation du travail 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 la législation du travail. Il a été construit en été 2011 au moyen du FMC (Focused Monolingual Crawler), développé dans le contexte de PANACEA. 

Le corpus contient 53 922 118 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 13 188 documents qui ont été crawlés depuis 1 015 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/kbv2-wp43
title: PoSTWITA dataset
title: PoSTWITA

description: The PoSTWITA dataset collects 6,738 tweets annotated with part of speech tags. The dataset has been used in the context of the PoSTWITA task (http://corpora.ficlit.unibo.it/PoSTWITA), organized as part of the EVALITA 2016 evaluation campaign (​​http://www.evalita.it/2016). The data are provided as plain text files in UNIX format and divided into development and test set (respectively, 6,438 and 300 tweets).
DOI: 10.57771/heqe-fq32
title: PRELEARN Dataset
title: PRELEARN

description: The PRELEARN dataset contains 6607 concept pairs and  a “Wikipedia pages file” containing the raw text of the Wikipedia pages referring to the concepts extracted (using WikiExtractor on a Wikipedia dump of Jan. 2020). The dataset has been used for the PRELEARN shared task (https://sites.google.com/view/prelearn20/), organised as part of Evalita 2020 evaluation campaign (http://www.evalita.it/2020). It was extracted from the ITA-PREREQ dataset (Miaschi et al., 2019), built upon the AL-CPL dataset (Liang et al., 2018), a collection of binary-labelled concept pairs extracted from textbooks on four domains: data mining, geometry, physics and pre-calculus. <p><p>The concept pairs consist of  target and prerequisite concepts (A, B), labelled as follows:<p>1 if B is a prerequisite of A;<p>0 in all other cases.<p><p>Domain experts were asked to manually annotate if pairs of concepts showed a prerequisite relation or not. The dataset is split into a training set (5908 pairs) and a test set (699 pairs). The distribution of prerequisite and non- prerequisite labels was balanced (50/50) for each domain only in the test datasets.<p>
DOI: 10.57771/49b8-e824
title: PTPARL Corpus
title: Corpus PTPARL

description: The PTPARL Corpus contains 1,076 texts consisting of adapted transcriptions of the Portuguese Parliament sessions. The corpus contains 1,000,441 tokens. <p><p>The corpus is delivered in one file, in two different formats. The txt version has one sentence per line, an identification number for each text and no further annotation. The cqpweb file is one token per line, followed by pos tag and lemma, and is annotated for NP chunks. The PTPARL Corpus is a subset of the Corpus of Reference of Contemporary Portuguese and follows the same annotation scheme. For more information on its preparation and annotation, see: Généreux, M., I. Hendrickx, A. Mendes (2012) “A Large Portuguese Corpus On-Line: Cleaning and Preprocessing”. In Caseli, H. et al. (eds.) Computational Processing of the Portuguese Language. Proceedings of the 10th International Conference PROPOR1012. Berlin, Heidelberg: Springer-Verlag, pp. 113-120.  <p>The Corpus is delivered with the annotation manual of the CRPC corpus, a metadata file and a narrative description of the resource.
description: Le corpus PTPARL est constitué de 1 076 textes consistant en des transcriptions adaptées des sessions du Parlement portugais. Le corpus contient 1 000 441 tokens. 

Le corpus est livré en un seul fichier, dans deux formats différents. La version txt contient une phrase par ligne, un numéro d’identification pour chaque texte et aucune autre annotation. Les fichier cqpweb contient un token par ligne, suivi par une étiquette de partie du discours et le lemme correspondant, avec l’annotation des chunks NP. Le corpus PTPARL est un sous-ensemble du Corpus de référence du portugais contemporain et suit le même schéma d’annotation. Pour plus d’informations sur sa préparation et son annotation, voir Généreux, M., I. Hendrickx, A. Mendes (2012) “A Large Portuguese Corpus On-Line: Cleaning and Preprocessing”. In Caseli, H. et al. (eds.) Computational Processing of the Portuguese Language. Proceedings of the 10th International Conference PROPOR1012. Berlin, Heidelberg: Springer-Verlag, pp. 113-120.
Le corpus est fourni avec le manuel d’annotation du corpus de référence, un fichier de meta-données et une description narrative de la ressource.
DOI: 10.57771/085j-nv61
title: QA4FAQ Dataset
title: QA4FAQ

description: The QA4FAQ dataset collects queries and FAQs collected from the application “AQP risponde”. It comprehends: a knowledge base of 406 FAQs; a set of 1,132 user queries; a set of 1,406 pairs < query, relevant faq >.<p>The dataset has been used in the context of the QA4FAQ task (http://qa4faq.github.io), organised as part of the EVALITA 2016 evaluation campaign (​​http://www.evalita.it/2016). The task concerns the retrieval of relevant frequently asked questions, given a user query.
DOI: 10.57771/qjpq-jm48
title: RudKorP - Serbian Public Mining Corpus
title: RudKorP

description: <p>Mining Corpus, specialized corpus in the field of mining and mineral resource exploitation, University of Belgrade, Faculty of Mining and Geology, Group for Language Technologies </p>
DOI: 10.57771/jrh9-0b74
title: SardiStance Dataset

description: The SardiStance dataset collects 3,242 tweets written in Italian about the “Movimento delle Sardine”, retrieved by means of the keywords “sardina”, “sardine” and homonymous hashtags between November 2019 and January 2020. The tweets were manually annotated for their stance, i.e. if they were against, in favour, neutral or out of the “Movimento delle sardine” topic.  In order to comply with GDPR privacy rules and Twitter’s policies, the identifiers of tweets and users have been anonymized and replaced by unique identifiers. The dataset has been produced and used in the context of the SardiStance task (http://www.di.unito.it/~tutreeb/sardistance-evalita2020/index.html) during the Evalita 2020 evaluation campaign (http://www.evalita.it/2020).
DOI: 10.57771/sjvh-a093
title: SardiStance Gold Labels

description: The SardiStance dataset collects tweets written in Italian about the “Movimento delle Sardine”, retrieved by means of the keywords “sardina”, “sardine” and homonymous hashtags between November 2019 and January 2020. The tweets were manually annotated for their stance, i.e. if they were against, in favour, neutral or out of the “Movimento delle sardine” topic.  In order to comply with GDPR privacy rules and Twitter’s policies, the identifiers of tweets and users have been anonymized and replaced by unique identifiers. The dataset has been produced and used in the context of the SardiStance task (http://www.di.unito.it/~tutreeb/sardistance-evalita2020/index.html) during the Evalita 2020 evaluation campaign (http://www.evalita.it/2020).<p>The present entry includes the gold labels for the test set (1110 tweets).
DOI: 10.57771/sy5j-v581
title: SardiStance Test Set

description: The SardiStance dataset collects tweets written in Italian about the “Movimento delle Sardine”, retrieved by means of the keywords “sardina”, “sardine” and homonymous hashtags between November 2019 and January 2020. The tweets were manually annotated for their stance, i.e. if they were against, in favour, neutral or out of the “Movimento delle sardine” topic.  In order to comply with GDPR privacy rules and Twitter’s policies, the identifiers of tweets and users have been anonymized and replaced by unique identifiers. The dataset has been produced and used in the context of the SardiStance task (http://www.di.unito.it/~tutreeb/sardistance-evalita2020/index.html) during the Evalita 2020 evaluation campaign (http://www.evalita.it/2020).<p>The present entry includes the test set (1110 tweets).
DOI: 10.57771/4cre-r316
title: SardiStance Training Set

description: The SardiStance dataset collects tweets written in Italian about the “Movimento delle Sardine”, retrieved by means of the keywords “sardina”, “sardine” and homonymous hashtags between November 2019 and January 2020. The tweets were manually annotated for their stance, i.e. if they were against, in favour, neutral or out of the “Movimento delle sardine” topic.  In order to comply with GDPR privacy rules and Twitter’s policies, the identifiers of tweets and users have been anonymized and replaced by unique identifiers. The dataset has been produced and used in the context of the SardiStance task (http://www.di.unito.it/~tutreeb/sardistance-evalita2020/index.html) during the Evalita 2020 evaluation campaign (http://www.evalita.it/2020).<p><p>The present entry includes the training set (2,132 tweets) and some contextual information regarding the tweet, the user and its social network.
DOI: 10.57771/mh3r-1a37
title: SENTIPOLC 2014 dataset
title: SENTIPOLC 2014

description: The SENTIPOLC 2014 dataset contains 6448 tweets annotated for subjectivity, sentiment polarity, and irony. <p>The dataset has been used in the context of the SENTIPOLC 2014 task (http://www.di.unito.it/~tutreeb/sentipolc-evalita14), organised as part of the EVALITA 2014 evaluation campaign (​​http://www.evalita.it/2014). It is split into a development set (4513 tweets) and a test set (1935 tweets). <p>In order to comply with GDPR privacy rules and Twitter’s policies, the identifiers of tweets and users have been anonymized and replaced by unique identifiers.
DOI: 10.57771/txy9-5e51
title: SENTIPOLC 2016 dataset
title: SENTIPOLC 2016

description: The SENTIPOLC 2016 dataset contains 9410 tweets annotated for subjectivity, overall and literal polarity, and irony. <p>The dataset has been created and used in the context of the SENTIPOLC 2016 task (http://www.di.unito.it/~tutreeb/sentipolc-evalita16/index.html), organized as part of the EVALITA 2016 evaluation campaign (​​http://www.evalita.it/2016). It is split into a development set (7410 tweets) and a test set (2000 tweets). <p>In order to comply with GDPR privacy rules and Twitter’s policies, the identifiers of tweets and users have been anonymized and replaced by unique identifiers.  <p>
DOI: 10.57771/4b2p-n272
title: Spanish Annotated Dictionary with Morphological and Linguistic Features
title: Spanish Annotated Dictionary

description: The Spanish Annotated Dictionary  consists of i) a limited size dictionary of Spanish words and ii) a language model for the Spanish language. The annotated dictionary provides useful information about words including chunking and syllabification as well as   grammatical information  such as “parts of speech”. The language model captures the journey of a student learning to read. It consists of a collection of language features that must be mastered by a reader. For each language feature, the model specifies its difficulty as well as a list of prerequisites that are typically mastered before the new feature is introduced in the learning path. What makes iRead Spanish  Annotated Dictionary special is the information associating each dictionary lemma with features in the language model. The iRead team of linguists and education researchers used rigorous research techniques informed by the latest science to develop the provided resources.
DOI: 10.57771/43mm-6p79
title: Spanish Festival HTS models - female speech
title: Modèles HTS en espagnol du projet Festival - voix de femme

description: This database contains the Festival HTS models trained with 10h of speech from the TC-STAR Spanish Baseline Female Speech Database (ELRA-S0309).
description: Cette base de données comprend les modèles HTS Festival entraînés à partir de 10 heures de parole de la voix de femme de référence TC-STAR espagnol (ELRA-S0309).
DOI: 10.57771/4qeq-rw73
title: Spanish Festival HTS models - male speech
title: Modèles HTS en espagnol du projet Festival - voix d'homme

description: This database contains the Festival HTS models trained with 10h of speech from the TC-STAR Spanish Baseline Male Speech Database (ELRA-S0310).
description: Cette base de données comprend les modèles HTS Festival entraînés à partir de 10 heures de parole de la voix d’homme de référence TC-STAR espagnol (ELRA-S0310).
DOI: 10.57771/5ma4-3h97
title: Speaking atlas of the regional languages of France
title: Atlas sonore des langues régionales de France

description: Directed by LIMSI (CNRS) with the support of the DGLFLF (Ministry of Culture and Communication), the Speaking atlas of the regional languages of France offers the same Aesop’s fable read in French and in a number of varieties of languages of France. This work, which has a scientific and heritage dimension, consists in highlighting the linguistic diversity of Metropolitan France and Overseas Territories, through recordings collected in the field and presented via an interactive map, with their orthographic transcription. As far as Occitan is concerned, about sixty varieties were collected in Gascony, Languedoc, Provence, northern Occitania and the Linguistic Crescent. Varieties of Basque, Breton, Franconian, West Flemish, Alsatian, Corsican, Catalan, Francoprovençal and Oïl language(s) are also provided, as well as about fifty languages in the French Overseas and non-territorial languages such as Rromani and the French sign language.
description: Réalisé par le LIMSI (CNRS) avec le soutien de la DGLFLF (Ministère de la Culture et de la Communication), l'Atlas sonore des langues régionales de France propose la même fable d'Ésope lue en français et en langues de France. Ce travail, qui possède une dimension scientifique et patrimoniale, consiste à mettre en valeur la diversité linguistique de la France hexagonale et des Outre-mer, à travers des enregistrements recueillis sur le terrain et présentés via une carte interactive, avec leur transcription orthographique. En ce qui concerne l'occitan, une soixantaine d'enregistrements a été collectée en Gascogne, Languedoc, Provence, dans le nord de l'Occitanie ainsi que dans la zone du Croissant. Des variétés de basque, breton, alsacien, francique, flamand occidental, corse, catalan, francoprovençal et langue(s) d'oïl sont également fournies, de même qu’une cinquantaine de langues dans les Outre-mer et des langues non-territoriales comme le rromani et la langue des signes française.
DOI: 10.57771/wwbw-7192
title: SrpCNNER - Named Entity Recognizer for Serbian (7 classes)
title: SrpCNNER

description: <p>A Named Entity Recognizer (NER) trained to recognize 7 different named entity types, with a Convolutional Neural Network (CNN) architecture, having F1 score of approx 91% on the test dataset. The NER tagset includes the 7 categories: demonyms (DEMO), professions and titles (ROLE), works of art (WORK), person names (PERS), places (LOC), events (EVENT) and organizations (ORG), as specified in the guidelines of the “Distant Reading for European Literary History” COST Action CA16204.</p>
DOI: 10.57771/xmbt-mp31
title: SrpELTeC-gold - Named Entity Recognition Training corpus for Serbian
title: SrpELTeC-gold

description: <p>The selection of 11 full novels and excerpts from 15 novels from Serbian literary corpus of novels written more than a century ago, have been automatically labelled with SrpNER system for Serbian  in the first stage of the gold standard preparation. Based on the specifically tailored guidelines, different evaluators performed careful checks and corrections, yielding a gold standard (SrpELTeC-gold). Corpus is annotated with 7 different named entity types: PERS, ROLE, LOC, DEMO, ORG, WORK, EVENT, as specified by Distant Reading for European Literary History (COST Action CA16204). Total number of text files is 242 with stend-off annotation in 242 .ann files. Total number of annotations is 330119, where PERS has 14788, ROLE has 10405, LOC has 1979, DEMO 1568, ORG 323, WORK 198, EVENT 149.</p>
DOI: 10.57771/tb02-h913
title: SrpKor4Tagging

description: <p>Corpus is created via mix of literary (⅓) and administrative (⅔) texts in Serbian.</p><p>It is tagged for POS for 2 tagsets: Universal POS tagset and SrpLemKor tagset (made according to traditional, descriptive Serbian grammar) and lemmatized</p><p> </p><p> </p>
DOI: 10.57771/fcm1-d806
title: SrpKor4Tagging-spaCy

description: <p>spaCy POS-tagging models for tagging using Universal POS and SrpLemKor tagsets, trained using the SrpKor4Tagging annotated corpora.</p>
DOI: 10.57771/q6an-py11
title: SrpKor4Tagging-TreeTagger

description: <p>TreeTagger models for tagging using Universal POS and SrpLemKor tagsets, trained using the SrpKor4Tagging annotated corpora and SrpMD4Tagging lexicons.</p>
DOI: 10.57771/8x7n-j886
title: SrpMD4Tagging - Serbian Morphological Dictionaries for Tagging
title: SrpMD4Tagging

description: <p>SrpMD4Tagging - Serbian Morphological Dictionaries for Tagging derived from Serbian Morphological Dictionaries (Krstev & Vitas)  as lookup dictionary for assigning lemma for given inflected form and POS tag. Two files for two POS tagsets available: Univesal Dependencies and traditional Serbian POS tagset.</p>