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3 results for “test corpus”
A Corpus of Arabic Literature (19-20th centuries) for Stylometric Tests
<p>The dataset contains three collections of mainly literary Arabic texts from the 19th and early 20th centuries.</p> <ul> <li><code>corpus022_JurjiZaydan_Dated</code> is a dated corpus of 22 historical novels by Jurjī Zaydān. It is well established that Jurjī Zaydān was publishing roughly one novel per year and the dates of publication are well known, which makes this corpus a valuable material for testing chronological changes in the style of individual writers.</li> <li><code>corpus065</code> is a corpus of 65 books by 8 authors;</li> <li><code>corpus300</code> contains 300 books by 28 authors;</li> </ul> <p>Texts have been collected from <a href="https://www.hindawi.org/">https://www.hindawi.org/</a>; the original EPUB files have been converted into clean text files (UTF8 encoding) and Arabic orthography has been normalized in the following manner: short vowels removed; the orthography of <em>alif</em> simplified (all <em>alif</em>s converted into bare <em>alif</em>s are used); <em>alif maqṣūraŧ</em>s converted to <em>yāʾ</em>s.</p> <p>For the names of authors and the names of works, the URIs follow the naming conventions used in the OpenITI project (<a href="https://github.com/openiti">https://github.com/openiti</a>, for the most up-to-date description, see <a href="https://kitab-project.org/corpus-and-data">https://kitab-project.org/corpus-and-data</a>). However, for better compatibility with R <code>stylo</code>, <em>underscore</em> (<code>_</code>) is used to connect URIs: AUTHOR_TITLE (in the dated Jurjī Zaydān corpus files are named YEAR_TITLE).</p>
MEDDOPROF corpus: test set
<p>The MEDDOPROF Shared Task tackles the detection of occupations and employment statuses in clinical cases in Spanish from different specialties. Systems capable of automatically processing clinical texts are of interest to the medical community, social workers, researchers, the pharmaceutical industry, computer engineers, AI developers, policy makers, citizen’s associations and patients. Additionally, other NLP tasks (such as anonymization) can also benefit from this type of data.</p> <p>MEDDOPROF has three different sub-tasks:</p> <p><strong>1) MEDDOPROF-NER</strong>: Participants must find the beginning and end of occupation mentions and classify them as PROFESION (PROFESSION), SITUACION_LABORAL (WORKING_STATUS) or ACTIVIDAD (ACTIVIDAD).</p> <p><strong>2) MEDDOPROF-CLASS: </strong>Participants must find the beginning and end of occupation mentions and classify them according to their referent (PACIENTE [patient], FAMILIAR [family member], SANITARIO [health professional] or OTRO [other]).</p> <p><strong>3) MEDDOPROF-NORM</strong>: Participants must find the beginning and end of occupation mentions and normalize them according to a reference codes list.</p> <p><strong>Please cite if you use this resource:</strong></p> <p>Salvador Lima-López, Eulàlia Farré-Maduell, Antonio Miranda-Escalada, Vicent Brivá-Iglesias and Martin Krallinger. NLP applied to occupational health: MEDDOPROF shared task at IberLEF 2021 on automatic recognition, classification and normalization of professions and occupations from medical texts. In Procesamiento del Lenguaje Natural, 67. 2021.</p> <pre><code>@article{meddoprof, title={NLP applied to occupational health: MEDDOPROF shared task at IberLEF 2021 on automatic recognition, classification and normalization of professions and occupations from medical texts}, author={Lima-López, Salvador and Farré-Maduell, Eulàlia and Miranda-Escalada, Antonio and Brivá-Iglesias, Vicent and Krallinger, Martin}, journal = {Procesamiento del Lenguaje Natural}, volume = {67}, year={2021}, issn = {1989-7553}, url = {http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6393}, pages = {243--256} }</code></pre> <p><strong>Resources:</strong></p> <p>- <a href="http://temu.bsc.es/meddoprof">Web</a></p> <p>- <a href="https://doi.org/10.5281/zenodo.5070540">Complete corpus</a></p> <p>- <a href="https://doi.org/10.5281/zenodo.4694768">Training Data</a></p> <p>- <a href="https://zenodo.org/record/4722741">Codes Reference List</a> (for MEDDOPROF-NORM)</p> <p>- <a href="https://zenodo.org/record/4720833">Annotation Guidelines</a></p> <p> </p> <blockquote> <p>MEDDOPROF is part of the IberLEF 2021 workshop, which is co-located with the SEPLN 2021 conference. For further information, please visit <a href="https://temu.bsc.es/meddoprof/">https://temu.bsc.es/meddoprof/</a> or email us at encargo-pln-life@bsc.es</p> <p>MEDDOPROF is promoted by the Plan de Impulso de las Tecnologías del Lenguaje de la Agenda Digital (Plan TL).</p> </blockquote>
Test Corpus
Test corpus for the evaluation of Crysl
ScienceDex guides
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.