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178 results for “Verbalization”
Bootstrapped Lexicon of German Verbal Polarity Shifters
<p>We provide a bootstrapped lexicon of German verbal polarity shifters. Our lexicon covers 2595 verbs of GermaNet. Polarity shifter labels are given for each word lemma. All labels were assigned by an expert annotator who is a native speaker of German.</p> <p><strong>Data</strong></p> <p>The data consists of two lists of GermaNet verbs annotated for whether they cause shifting:</p> <ol> <li><code>verbal_shifters.gold_standard.txt</code>: The initial gold standard (§3) of 2000 randomly sampled verbs.</li> <li><code>verbal_shifters.bootstrapping.txt</code>: The bootstrapped 595 verbs (§5.3) that were labelled as shifters by our best classifier and then manually annotated.</li> </ol> <p><strong>Format</strong></p> <p>Each line contains a verb and its label, separate by a whitespace.</p> <p><strong>Attribution</strong></p> <p>This dataset was created as part of the following publication:</p> <p>Marc Schulder, Michael Wiegand, Josef Ruppenhofer (2018). <strong>"Automatically Creating a Lexicon of Verbal Polarity Shifters: Mono- and Cross-lingual Methods for German"</strong>. <em>Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018)</em>. Santa Fe, New Mexico, USA, August 20 - August 26, 2018. <a href="https://doi.org/10.5281/zenodo.3365694">DOI: 10.5281/zenodo.3365694</a>.</p> <p>If you use the data in your research or work, please cite the publication.</p>
Lexicon of English Verbal Polarity Shifters
<p>We provide a complete lexicon of English verbal polarity shifters and their shifting scope. Our lexicon covers all verbs of WordNet v3.1 that are single word or particle verbs. Polarity shifter and scope labels are given for each lemma-synset pair (i.e. each word sense of a lemma).</p> <p><strong>Data</strong></p> <p>The data is presented in the following forms:</p> <ol> <li>A complete lexicon of all verbal shifters and their shifting scopes.</li> <li>Two auxiliary lists: <ol> <li>A list of all lemmas with shifter labels</li> <li>A list of all word senses with shifter labels</li> </ol> </li> </ol> <p>All files are in CSV (comma-separated value) format.</p> <p><strong>1. Main Lexicon</strong></p> <p>File name: <code>shifter_lexicon.csv</code></p> <p>The main lexicon lists all verbal shifters and their shifting scopes. Verbal shifters are modelled as lemma-sense pairs with one or more shifting scopes.</p> <p>Each line of the lexicon file contains a single lemma-sense-scope triple, using the format:</p> <pre><code>LEMMA,SYNSET,SCOPE </code></pre> <p>The elements are defined as follows:</p> <ul> <li><strong>LEMMA:</strong> The lemma form of the verb.</li> <li><strong>SYNSET:</strong> The numeric identifier of the synset, commonly referred to as <em>offset</em> or <em>database location</em>. It consists of 8 digits, including leading zeroes (e.g. 00334568).</li> <li><strong>SCOPE:</strong> The scope of the shifting: <ul> <li><code>subj</code>: The verbal shifter affects its subject.</li> <li><code>dobj</code>: The verbal shifter affects its direct object.</li> <li><code>pobj_*</code>: The verbal shifter affects objects within a prepositional phrase. The preposition in question is included in the annotation. For example a <em>from</em>-preposition scope receives the label <code>pobj_from</code> and a a <em>for</em>-preposition receives <code>pobj_for</code>.</li> <li><code>comp</code>: The verbal shifter affects a clausal complement, such as infinitive clauses or gerunds.</li> </ul> </li> </ul> <p>The lexicon lists all lemma-sense pairs that are verbal shifters. Any lemma-sense pair not listed is not a verbal shifter. When a lemma-sense pair has more than one possible scope, a separate entry is made for each scope.</p> <p><strong>2. Auxiliary Lists</strong></p> <p>The auxiliary files represent the same shifter information as the main lexicon, but for lemmas and synsets, respectively, instead of for lemma-sense pairs. Due to their nature, these lists are more coarse-grained than the main lexicon and contain no information on shifter scope. They are provided as a convenience for fast experimentation.</p> <p><strong>2.1. List of Lemmas</strong></p> <p>File name: <code>shifter_lemma_lexicon.csv</code></p> <p>List of all verb lemmas and whether they are shifters in at least one of their word senses.</p> <pre><code>LEMMA,LABEL </code></pre> <ul> <li><strong>LEMMA:</strong> The lemma form of the verb.</li> <li><strong>LABEL:</strong> <code>shifter</code> if the verb is a shifter in at least one of its word senses, otherwise <code>nonshifter</code>.</li> </ul> <p>Many verbal shifter lemmas only cause shifting in some of their word senses. This list is therefore considerably more coarse-grained than the main lexicon.</p> <p><strong>2.2. List of Synsets</strong></p> <p>File name: <code>shifter_synset_lexicon.csv</code></p> <p>List of all synsets and whether their lemmas are shifters in this specific word sense.</p> <pre><code>SYNSET,LABEL </code></pre> <ul> <li><strong>SYNSET:</strong> The numeric identifier of the synset, commonly referred to as <em>offset</em> or <em>database location</em>. It consists of 8 digits, including leading zeroes (e.g. 00334568).</li> <li><strong>LABEL:</strong> <code>shifter</code> if the word sense causes shifting, otherwise <code>nonshifter</code>.</li> </ul> <p>Shifting is shared among lemmas of the same word sense. This list, therefore, provides (almost) the same granularity for the shifter label as the main lexicon. However, in a few exceptions, synsets contained words with subtly different senses that did not all cause shifting. These senses are considered shifters in this list, analogous to the generalisation in the list of lemmas.</p> <p><strong>Attribution</strong></p> <p>This dataset was created as part of the following publication:</p> <p>Schulder, Marc and Wiegand, Michael and Ruppenhofer, Josef and Köser, Stephanie (2018). <strong>"Introducing a Lexicon of Verbal Polarity Shifters for English"</strong>. Proceedings of the 11th Conference on Language Resources and Evaluation (LREC). Miyazaki, Japan, May 7-12, 2018. <a href="https://doi.org/10.5281/zenodo.3365683">DOI: 10.5281/zenodo.3365683</a>.</p> <p>If you use the data in your research or work, please cite the publication.</p>
Bootstrapped Lexicon of English Verbal Polarity Shifters
<blockquote> <p>An extended version of this dataset that also covers nominal and adjectival polarity shifters can be found at <a href="https://doi.org/10.5281/zenodo.3365601">doi:10.5281/zenodo.3365601</a>.</p> </blockquote> <p> </p> <p>We provide a bootstrapped lexicon of English verbal polarity shifters. Our lexicon covers 3043 verbs of WordNet v3.1 (Miller et al., 1990) that are single word or particle verbs. Polarity shifter labels are given for each word lemma.</p> <p><strong>Data</strong></p> <p>The data consists of:</p> <ol> <li>Two lists of WordNet verbs (Miller et al., 1990), annotated for whether they cause shifting. <ol> <li>The initial gold standard (§2) of 2000 randomly chosen verbs.</li> <li>The bootstrapped 1043 verbs (§5.3) that were labelled as shifters by our best classifier and then manually annotated.</li> </ol> </li> <li>Data set of verb phrases from the Amazon Product Review Data corpus (Jindal & Liu, 2008), annotated for polarity of phrase and polar noun.</li> </ol> <p> </p> <p><strong>1. Verbal Shifters</strong></p> <p><strong>Files</strong></p> <ul> <li>The initial gold standard: <code>verbal_shifters.gold_standard.txt</code></li> <li>The bootstrapped verbs: <code>verbal_shifters.bootstrapping.txt</code></li> </ul> <p><strong>Format</strong></p> <ul> <li>Each line contains a verb and its label, separate by a whitespace.</li> <li>Multiword expressions are separated by an underscore (WORD_WORD).</li> <li>All labels were assigned by an expert annotator.</li> </ul> <p> </p> <p><strong>2. Sentiment Verb Phrases</strong></p> <p><strong>Files</strong></p> <ul> <li>All annotated verb phrases: <code>sentiment_phrases.txt</code></li> </ul> <p><strong>Content</strong></p> <p>The file starts with 400 phrases containing shifter verbs, followed by 2231 phrases containing non-shifter verbs.</p> <p><strong>Format</strong></p> <p>Every item consists of:</p> <ul> <li>The sentence from which the VP and the polar noun were extracted.</li> <li>The VP, polar noun and the verb heading the VP.</li> <li>Constituency parse for the VP.</li> <li>Gold labels for VP and polar noun by a human annotator.</li> <li>Predicted labels for VP and polar noun by RNTN tagger (Socher et al., 2013) and <code>LEX_gold</code> approach.</li> <li>Items are separated by a line of asterisks (*)</li> </ul> <p><strong>Related Resources</strong></p> <ul> <li><strong>Paper:</strong> <a href="https://aclweb.org/anthology/I17-1063">ACL Anthology</a> or <a href="https://doi.org/10.5281/zenodo.3365609">DOI: 10.5281/zenodo.3365609</a></li> <li><strong>Presentation:</strong> <a href="https://www.aclweb.org/anthology/attachments/I17-1063.Presentation.pdf">ACL Anthology</a></li> <li><strong>Word Embedding:</strong> <a href="https://doi.org/10.5281/zenodo.3370051">DOI: 10.5281/zenodo.3370051</a></li> </ul> <p><strong>Attribution</strong></p> <p>This dataset was created as part of the following publication:</p> <p>Marc Schulder, Michael Wiegand, Josef Ruppenhofer and Benjamin Roth (2017). <strong>"Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features"</strong>. Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP). Taipei, Taiwan, November 27 - December 3, 2017. <a href="https://doi.org/10.5281/zenodo.3365609">DOI: 10.5281/zenodo.3365609</a>.</p> <p>If you use the data in your research or work, please cite the publication.</p> <p> </p>
"Talking Stick" and Other Verbal Turn-taking Strategies
<p>The following data’ adapted and reconstructed because I see conventional strategies in teaching foreign languages to non-native speakers, can still be effective and efficient as long as the accuracy of the use of the teaching focus is measured. The inspiration for collecting this data, I accidentally saw one of the published scientific articles on literacy, which uses the TS (talking stick) technique to improve communication skills while strengthening the ability to remember, understand, and practice vocabulary in communication using English. Therefore data was converted to voice data which does not detract from the main point of the second scientific source' while the strategy explained can be found below the section, then the audio format is displayed in mp3 formats separately.</p>
Children's Reliance on the Non-Verbal Cues of a Robot Versus a Human
<p>This study assessed whether four- to six-year-old children (i) differed in their weighing of non-verbal cues (pointing, eye gaze) and verbal cues provided by a robot versus a human; (ii) weighed non-verbal cues differently depending on whether these contrasted with a novel or familiar label; and (iii) relied differently on a robot’s nonverbal cues depending on the degree to which they attributed human-like properties to the robot. The results showed that children generally followed pointing over labeling, in line with earlier research. Children did not rely more strongly on the non-verbal cues of a robot versus those of a human. Regarding pointing, children who perceived the robot as human-like relied on pointing more strongly when it contrasted with a novel label versus a familiar label, but children who perceived the robot as less human-like did not show this difference. Regarding eye gaze, children relied more strongly on the gaze cue when it contrasted with a novel versus a familiar label, and no effect of anthropomorphism was found. Taken together, these results show no difference in the degree to which children rely on non-verbal cues of a robot versus those of a human and provide preliminary evidence that differences in anthropomorphism may interact with children’s reliance on a robot’s non-verbal behaviors.</p>
Dataset from 'The verbal morphology of Yonghe Qiang: an Eastern Himalayan Language
<p>The following is a data set that includes links to the recordings of the data referenced in the dissertation. This data set will be improved upon as more links to the corpus in ELAR are added. </p>
Database of the assessment of two instructional design variables in verbal reasoning and mathematical reasoning courses from the perspective of a Peruvian pre-university center students
<p>These are the data obtained from 4 evaluations made to a sample of 630 students of a Peruvian pre-university center. First, two study variables were evaluated: teaching sequence compliance and the student's educational need according to the perspective of 315 students of the verbal reasoning course. Second, the same study variables were assessed in the remaining 315 students of the mathematical reasoning course. This information is being used in research to obtain an academic degree and later to make a publication of a scientific article.</p> <p>For the treatment of these data, inferential statistics was used through the software R version 3.4.4 (2018) The R Foundation for Statistical Computing.</p>
Improving Methods to Measure Comparable Mortality by Cause - Gold Standard Verbal Autopsy Data 2011-2014
<p>These data were collected and compiled as part of the Improving Methods to Measure Comparable Mortality by Cause (IMMCMC) project, funded by Australia's National Health and Medical Research Council (NHMRC). Verbal autopsies (VAs) were conducted between 2011 and 2014 in three sites: Bohol, Philippines; Chandpur and Comila Districts, Bangladesh; and Central and Eastern Highlands Provinces, Papua New Guinea. Diagnostic criteria and cause lists similar to those employed in the Population Health Metrics Research Consortium (PHMRC) study were used to identify gold standard (GS) deaths. This study added 3512 deaths (2491 adults, 320 children, and 701 neonates) to the GS VA database created from the PHMRC study. This dataset contains the combined PHMRC and IMMCMC data for an updated GS VA database.</p>
Verbal and nominal complexity and sociolinguistic environment
<p>This material contains the dataset from the <a href="https://version.helsinki.fi/hals/sinnemaki/sinnemaki-digarbo2018">gitlab repository</a> of the following article. Please cite the article when using the data.</p> <p>Sinnemäki, Kaius and Francesca Di Garbo. 2018. Language structures may adapt to the sociolinguistic environment, but it matters what and how you count: A typological study of verbal and nominal complexity. <em>Frontiers in Psychology</em> 9: 1141.</p>
Tables of verbal derivatives in -š- in the Saami languages
<p>The tables present the occurrence of verbs with a suffixal <em>-š- (-šš-)</em> by tabulating the attested derivatives across the Saami languages. Base words are given in their North Saami form by default, including approximate meanings in Finnish or the language used in sources in question. The corresponding entry number of Eliel Lagercranz's Lappischer Wortschatz (1939) is also given when applicable. For more information about sources etc., see the paper to which this is an appendix:</p> <p>Kuokkala, Juha & Koponen, Eino. 2023. On the distribution and history of Saami verbal derivatives in <em>-š-</em>. <em>Journal of Estonian and Finno-Ugric Linguistics </em>14(3). 73–105. <a href="https://doi.org/10.12697/jeful.2023.14.3.03">https://doi.org/10.12697/jeful.2023.14.3.03</a></p>
Supplementary material to: Russian verbal aspect and the activation of event knowledge: Processing typical and atypical location adverbials in perfective and imperfective sentences
<p>Supplementary material for a self-paced reading experiment:</p> <ol> <li>Material: contains the verbal stimuli (experimental and filler sentences)</li> <li>raw_data.zip: E-Prime output for all 50 participants (tab-separated txt-files)</li> <li>spr_aspect_respinf.txt: Basic information on the participants; tab-separated txt-file</li> <li>spr_aspect_preprocessing_subm2_fin.R: data preprocessing and calculation of correct responses per speaker in R; R script<br>Input: <br>- Files from the "raw_data"-folder<br>- spr_aspect_respinf.txt<br>Output: <br>- spr_aspect_respinf_corr_resp.txt: same as spr_aspect_respinf.txt + number of correct responses per participant; tab-separated txt-file<br>- spr_aspect_all.txt: relevant data from all participants in one file; tab-separated txt-file<br>- spr_aspect_all_without-outlier.txt: same as spr_aspect_all.txt, but outliers set to NA; tab-separated txt-file</li> <li>spr_aspect_figures-stats_subm2_fin.R: plots figures and calculates statistics (descriptive statistics and GLMM) in R, R script<br>Input: <br>- spr_aspect_all_without-outlier.txt<br>Output:<br>- spr_aspect_avg.txt: Mean RT and SD per condition; tab-separated txt-file<br>- Figures</li> </ol>
Classical Tibetan Verbal Paradigms
<p>This is a collection of verb paradigms in Classical Tibetan (Written Tibetan), conforming to the Paralex (https://www.paralex-standard.org) standard. The metadata conforms to the Frictionless (https://frictionlessdata.io/) standard. Datafiles are encoded as csv files.</p>
VeLeCa: a Verbal Lexicon of Catalan
<p>VeLeCa is an inflected lexicon of Catalan verbal inflection containing the phonological form of 174,200 word forms from 3,484 lexemes and their respective lexical and morphosyntactic values and frequencies.</p>
VeLeRo: a Verbal Lexicon of Romanian
<p>VeLeRo, an inflected lexicon of Standard Romanian which contains the full paradigm of 7297 verbs in phonological form, with lemma-level and cell-level frequencies.</p> <p>Full info at: Herce, B., Pricop, B. VeLeRo: an inflected verbal lexicon of standard Romanian and a quantitative analysis of morphological predictability. <em>Lang Resources & Evaluation</em> (2024). https://doi.org/10.1007/s10579-024-09721-3</p>
English-Portuguese Dictionary of Verbal Collocations
<p>This is the json-LD version of the data of Tagnin's <strong>English-Portuguese Dictionary of Verbal Collocation</strong>s, which is available as a proof-of-concept interactive resource at <a href="https://mangalamresearch.shinyapps.io/EnglishPortugueseVerbalCollocations/" target="_blank" rel="nofollow noopener noreferrer">https://mangalamresearch.shinyapps.io/EnglishPortugueseVerbalCollocations/</a> .</p> <p>This is still work in progress; comments and suggestions are most welcome. Contact me at seotagni@gmail.com.</p> <p>The conversion of the dictionary data and its display in the form of a digital dictionary were made possible thanks Ligeia Lugli, Tilak Balavijayan and the NEH-funded project <em>Democratizing Digital Lexicography</em> (HAA-290402-23).</p> <p>For more information about the criteria adopted in the dictionary, please go to the Word file included in this repository.</p> <p> </p>
EWAS associations between DNAm and general cognitive score, perceptive performance score, and verbal score
<p><strong><span>Evaluating the association between placenta DNA methylation and cognitive functions in the offspring </span></strong></p> <p><a name="_Hlk141095040"></a><span>Placenta plays a crucial role protecting the foetus from environmental harm and supports the development of its brain. In fact, compromised placental function could predispose an individual to neurodevelopmental disorders</span><span><span>. Placental epigenetic modifications, including DNA methylation, could be considered a proxy of placental function and thus plausible mediators of the association between intrauterine environmental exposures and genetics, and childhood and adult mental health. Although neurodevelopmental disorders such as autism spectrum disorder have been investigated in relation to placenta DNA methylation, no studies have addressed the association between placenta DNA methylation and child’s cognitive functions. </span><span>Thus, our goal here was to investigate whether placental DNA methylation profile measured using the Illumina EPIC array is associated with three different cognitive domains (namely verbal score, perceptive performance score, and general cognitive score) assessed by the McCarthy Scales of Children’s functions in childhood at age 4. To this end, we conducted epigenome-wide association analyses including data from 255 mother-child pairs within the INMA project and performed a follow-up functional analysis to help the interpretation of the findings. After multiple-testing correction, we found that methylation at 4 CpGs (cg1548200, cg02986379, cg00866476 and cg14113931) was significantly associated with the general cognitive score, and 2 distinct differentially methylated regions (DMRs) (including 27 CpGs) were significantly associated with each cognitive dimension. <a name="_Hlk168395284"></a><a name="_Hlk168394861"></a><span>Interestingly, the genes annotated to these CpGs, <span>such as <em>DAB2, CEP76</em>, <em>PSMG2,</em> or <em>MECOM,</em> </span>are involved in placenta, foetal, and brain development</span><span>. </span>Moreover, functional enrichment analyses of suggestive CpGs (<em>p</em><1x10<sup>-4</sup>) revealed gene-sets involved in placenta development, foetus formation and brain growth. These findings suggest that placental DNAm could be a mechanism contributing to the alteration of important pathways in the placenta that have a consequence on the offspring’s brain development and cognitive function. </span></span></p>
AraVeLex: Modern Standard Arabic Verbal lexicon
<p>Paralex lexicon of Modern Standard Arabic Verbs, providing inflected forms in orthography and phonemic transcription.</p>
The cultural transmission of causally (ir)relevant actions in the laboratory: Does modelling or verbal instruction lead to greater copying fidelity?
<p>This study examines the fidelity with which adults vs. children transmit a set of actions within diffusion chains (generations 1 to 3). The set consisted of causally relevant and causally irrelevant actions. Half of the adult and half of the child chains transmitted the actions via demonstration (next participant saw the previous perform the actions on video); the other half transmitted them verbally (next participant listened to audio file the previous participant describe his/her actions). We measured whether the actions were retained (i.e. re-produced by each next participant in the chain).</p>
Creatividad verbal y comprensión lectora en escolares del quinto grado de primaria de una institucion educativa estatal: Callao
<p>La matriz de datos contiene las siguientes variables: Estudiantes, Edad, Sexo, Sección, Institución educativa, Flexibilidad y comprensión lectora y 50 casos.</p>
Memoria verbal inmediata y conciencia fonológica en niños de 5 años de una institución educativa inicial de Bellavista
<p>La matriz de datos contiene las siguientes variables: Género, Memoria Verbal inmediata, Conciencia fonológica, Conciencia Léxica, Conciencia Fonémica, Conciencia Silábica y 120 casos.</p>
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