cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35111/y013-n255
title: NewSoMe Corpus of Opinion in News Reports

description: <h3>Introduction</h3><br>
<p>NewSoMe Corpus of Opinion in News Reports was compiled at <a href="http://www.barcelonamedia.org/">Barcelona Media</a> and consists of Spanish, Catalan and Portuguese news reports annotated for opinions. It is part of the NewSoMe (News and Social Media) set of corpora presenting opinion annotations across several genres and covering multiple languages. NewSoMe is the result of an effort to build a unifying annotation framework for analyzing opinion in different genres, ranging from controlled text, such as news reports, to diverse types of user-generated content that includes blogs, product reviews and microblogs.</p><br>
<h3>Data</h3><br>
<p>The source data in this release was obtained from various newspaper websites and consists of approximately 200 documents in each of Spanish, Catalan and Portuguese. The annotation was carried out manually through the crowdsourcing platform <a href="http://www.crowdflower.com/">CrowdFlower</a> with seven annotations per layer that were aggregated for this data set. The layers annotated were topic, segment, cue, subjectivity, polarity and intensity.</p><br>
<p>Data is presented as UTF-8 either as plain text or in CSV files.</p><br>
<h3>Samples</h3><br>
<p>Please view the following samples.</p><br>
<ul><br>
<li><a href="desc/addenda/LDC2015T17.pt.txt">Portuguese Raw</a></li><br>
<li><a href="desc/addenda/LDC2015T17.sp.sent.csv">Spanish Sentences</a></li><br>
<li><a href="desc/addenda/LDC2015T17.ca.topic.csv">Catalan Topics</a></li><br>
</ul><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2015 Fundacío Barcelona Media, © 2015 Trustees of the University of Pennsylvania
DOI: 10.35111/6xhy-6a11
title: ACE 2007 Spanish DevTest - Pilot Evaluation

description: <h3>Introduction</h3><br>
<p>ACE 2007 Spanish DevTest was developed by the Linguistic Data Consortium (LDC). This publication contains the complete set of Spanish development and test data to support the <a href="http://www.itl.nist.gov/iad/mig/tests/ace/2007/">2007 Automatic Content Extraction (ACE) technology evaluation</a>, namely, newswire data annotated for entities and temporal expressions.</p><br>
<p>The objective of the ACE program was to develop automatic content extraction technology to support automatic processing of human language in text form from a variety of sources including newswire, broadcast programming and weblogs. In the 2007 evaluation, participants were tested on system performance for the recognition of entities, values, temporal expressions, relations, and events in Chinese and English and for the recognition of entities and temporal expressions in Arabic and Spanish. LDC's work in the ACE program is described in more detail on the LDC <a href="https://www.ldc.upenn.edu/collaborations/past-projects/ace">ACE project</a> pages.</p><br>
<p>LDC has also released ACE 2007 Multilingual Training Corpus (<a href="../../../LDC2014T18">LDC2014T18</a>) which contains the Arabic and Spanish training data used in the 2007 evaluation.</p><br>
<h3>Data</h3><br>
<p>The data consists of newswire material published in May 2005 from the following sources: Agence France Press, The Associated Press and Xinhua News Agency.</p><br>
<p>All files were annotated by two human annotators working independently. Discrepancies between the two annotations were adjudicated by a senior team member resulting in a gold standard file.</p><br>
<p>There are three annotation directories for each newswire story that contain an identical copy of the source text in SGML format and two associated annotated versions in XML format and tab delimited format. All text is UTF-8 encoded.</p><br>
<h3>Samples</h3><br>
<p>Please view the following samples:</p><br>
<ul><br>
<li><a href="desc/addenda/LDC2015T20.ag.xml.jpg">AG XML</a></li><br>
<li><a href="desc/addenda/LDC2015T20.apf.xml.jpg">APF xml</a></li><br>
<li><a href="desc/addenda/LDC2015T20.sgm.jpg">SGML</a></li><br>
<li><a href="desc/addenda/LDC2015T20.tab.txt">TAB</a></li><br>
</ul><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2005 Agence France Presse, The Associated Press, Xinhua News Agency, © 2005, 2007, 2015 Trustees of the University of Pennsylvania
DOI: 10.35111/13mf-v667
title: Karlsruhe Children's Text

description: <h3>Introduction</h3><br>
<p>Karlsruhe Children's Text was developed by the <a href="http://www.dhbw.de/english/dhbw/about-us.html">Cooperative State University Baden-W&uuml;rttemberg</a>, <a href="http://www.ph-karlsruhe.de/index.php?id=5829">University of Education</a> and <a href="https://www.kit.edu/english/">Karlsruhe Institute of Technology</a>. It consists of over 14,000 freely written, German sentences from more than 1,700 school children in grades one through eight.</p><br>
<p>The data collection was conducted in 2011-2013 at elementary and secondary schools in and around Karlsruhe, Germany. Students were asked to write as verbose a text as possible. Those in grades one to four were read two stories and were then asked to write their own stories. Students in grades five through eight were instructed to write on a specific theme, such as "Imagine the world in 20 years. What has changed?"</p><br>
<p>The goal of the collection was to use the data to develop a spelling error classification system.</p><br>
<h3>Data</h3><br>
<p>Annotators converted the handwritten text into digital form with all errors committed by the writers; they also created an orthographically correct version of every sentence. Metadata about the text was gathered, including the circumstances under which it was collected, information about the student writer and background about spelling lessons in the particular class. In a second step, the students' spelling errors were annotated into general groupings: grapheme level, syllable level, morphology and syntax. The files were anonymized in a third step.</p><br>
<p>This release also contains metadata regarding the writers&rsquo; language biography, teaching methodology, age, gender and school year. The average age of the participants was 11 years, and the gender distribution was nearly equal.</p><br>
<p>Original handwriting is presented as JPEG format image files and the converted annotated text as UTF-8 plain text. Metadata is contained within each text file.</p><br>
<h3>Samples</h3><br>
<p>Please view these <a href="desc/addenda/LDC2015T22.jpg">image</a> and <a href="desc/addenda/LDC2015T22.txt">text</a> samples.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p><br>
<h3>Additional Citation</h3><br>
<p>Users should cite this <a href="../../../docs/LDC2015T22/L1TLT_Data_Lavalley_Final.pdf">paper </a>in any publication that describes this corpus.</p><br>
<p>Preparing Children's Writing Database for Automated Processing<br />R&eacute;mi Lavalley, Kay Berkling, Sebastian St&uuml;ker,<br />Workshop on Language Teaching, Learning and Technology (LTLT)<br />Leipzig, September 4, 2015</p></br>
Portions © 2015 Dr. Johanna Fay, © 2015 Trustees of the University of Pennsylvania
DOI: 10.35111/vc52-tm53
title: KHATT: Handwritten Arabic Text

description: <h3>Introduction</h3><br>
<p>KHATT: Handwritten Arabic Text was developed by <a href="http://www.kfupm.edu.sa/default.aspx">King Fahd University of Petroleum & Minerals</a>, <a href="http://www.tu-dortmund.de/uni/International/index.html">Technical University of Dortmund</a> and <a href="https://www.tu-braunschweig.de/">Braunschweig University of Technology</a>. It is comprised of scanned Arabic handwriting from 1,000 distinct male and female writers representing diverse countries, age groups, handedness and education levels. Participants produced text on a topic of their choice in an unrestricted style. KHATT was designed to promote research in areas such as text recognition and writer identification.</p><br>
<h3>Data</h3><br>
<p>The majority of participants were natives of Saudi Arabia; the next largest group was from a collection of regional countries (Egypt, Jordan, Kuwait, Morocco, Palestine, Tunisia and Yemen). Most writers were between 16-25 years of age with high school or university qualifications.</p><br>
<p>Scanned text is presented as tiff images scanned at 200, 300 and 600 DPI (dots per inch). The source images are four-page tiffs consisting of metadata about the writer, fixed paragraphs and free writing. Image files of isolated paragraphs or lines are also included. Ground-truth files are presented as plain-text Unicode. Data is divided into training, validation and test sets.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2015T23.tif">image sample</a> and this <a href="desc/addenda/LDC2015T23.txt">text sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2015 King Fahd University of Petroleum & Minerals, Trustees of the University of Pennsylvania
DOI: 10.35111/y7p6-nk41
title: GALE Phase 4 Chinese Newswire Parallel Sentences

description: <h3>Introduction</h3><br>
<p>GALE Phase 4 Chinese Newswire Parallel Sentences was developed by the Linguistic Data Consortium (LDC). Along with other corpora, the parallel text in this release comprised training data for Phase 4 of the DARPA GALE (Global Autonomous Language Exploitation) Program. This corpus contains Chinese source sentences and corresponding English translations selected from newswire data collected by LDC in 2008 and translated by LDC or under its direction.</p><br>
<h3>Data</h3><br>
<p>GALE Phase 4 Chinese Newswire Parallel Sentences includes 627 source-translation document pairs, comprising 90,434 tokens of Chinese source text and its English translation. Data is drawn from six distinct Chinese newswire sources.</p><br>
<p>Sentences were selected for translation in two steps. First, files were chosen using sentence selection scripts provided by GALE program participants <a href="http://www.sri.com/">SRI International</a> and <a href="http://www.ibm.com/us/en/">IBM</a>. The output was then manually reviewed by LDC staff to eliminate problematic sentences. Selected files were reformatted into a human-readable translation format and assigned to translation vendors. Translators followed LDC's Chinese to English translation guidelines and were provided with the full source documents containing the target sentences for their reference. Bilingual LDC staff performed quality control procedures on the completed translations.</p><br>
<p>Source data and translations are distributed in TDF format. TDF files are tab-delimited files containing one segment of text along with meta information about that segment. Each field in the TDF file is described in TDF_format.txt. All data are encoded in UTF-8.</p><br>
<h3>Acknowledgement</h3><br>
<p>This work was supported in part by the Defense Advanced Research Projects Agency, GALE Program Grant No. HR0011-06-1-0003. The content of this publication does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.</p><br>
<h3>Samples</h3><br>
<p>Please view the following samples.</p><br>
<ul><br>
<li><a href="desc/addenda/LDC2015T24.jpg">Chinese Source</a></li><br>
<li><a href="desc/addenda/LDC2015T24.cmn.sel.jpg">Chinese Selected Sentences</a> (Source data selected for translation)</li><br>
<li><a href="desc/addenda/LDC2015T24.sel.eng.txt">Selection English</a> (Translated data)</li><br>
</ul><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2008 Agence France Presse, China Military Online, Chinanews.com, Guangming Daily, Peoples Daily, Xinhua News Agency, © 2008, 2015 Trustees of the University of Pennsylvania
DOI: 10.35111/q015-fr05
title: GALE Phase 3 Chinese Broadcast News Transcripts

description: <h3>Introduction</h3><br>
<p>GALE Phase 3 Chinese Broadcast News Transcripts was developed by the Linguistic Data Consortium (LDC) and contains transcriptions of approximately 150 hours of Chinese broadcast news speech collected in 2007 and 2008 by LDC and Hong University of Science and Technology (HKUST), Hong Kong, during Phase 3 of the DARPA GALE (Global Autonomous Language Exploitation) Program.</p><br>
<p>Corresponding audio data is released as GALE Phase 3 Chinese Broadcast News Speech (<a href="../../../LDC2015S13">LDC2015S13</a>).</p><br>
<p>The broadcast news recordings for transcription feature news broadcasts focusing principally on current events from the following sources: Anhui TV, a regional television station in Mainland China, Anhui Province; China Central TV (CCTV), a national and international broadcaster in Mainland China; Phoenix TV, a Hong Kong-based satellite television station; and Voice of America (VOA), a U.S. government-funded broadcast programmer.</p><br>
<h3>Data</h3><br>
<p>The transcript files are in plain-text, tab-delimited format (TDF) with UTF-8 encoding, and the transcribed data totals 1,933,695 tokens. The transcripts were created with the LDC-developed transcription tool, XTrans, a multi-platform, multilingual, multi-channel transcription tool that supports manual transcription and annotation of audio recordings. XTrans is available from the following link, <a href="https://www.ldc.upenn.edu/language-resources/tools/xtrans">https://www.ldc.upenn.edu/language-resources/tools/xtrans</a>.</p><br>
<p>The files in this corpus were transcribed by LDC staff and/or by transcription vendors under contract to LDC. Transcribers followed LDC's quick transcription guidelines (QTR) and quick rich transcription specification (QRTR) both of which are included in the documentation with this release. QTR transcription consists of quick (near-) verbatim, time-aligned transcripts plus speaker identification with minimal additional mark-up. It does not include sentence unit annotation. QRTR annotation adds structural information such as topic boundaries and manual sentence unit annotation to the core components of a quick transcript. Files with QTR as part of the filename were developed using QTR transcription. Files with QRTR in the filename indicate QRTR transcription.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2015T25.txt">text sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p><br>
<h3>Acknowledgement</h3><br>
<p>This work was supported in part by the Defense Advanced Research Projects Agency, GALE Program Grant No. HR0011-06-1-0003. The content of this publication does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.</p></br>
Portions © 2007 Anhui TV, © 2007 China Central TV, © 2007, 2008 Phoenix TV, © 2007, 2008, 2015 Trustees of the University of Pennsylvania
DOI: 10.35111/ygn0-wm25
title: CHM150

description: <h3>Introduction</h3><br>
<p>CHM150 (Corpus Hecho en M&eacute;xico 150) was developed by the <a href="http://odin.fi-b.unam.mx/profesores/abelherrera/">Speech Processing Laboratory</a> of the Faculty of Engineering at the <a href="http://www.unam.mx/">National Autonomous University of Mexico</a> (UNAM) and consists of approximately 1.63 hours of Mexican Spanish speech, associated transcripts, and speaker metadata. The goal of this work was to support spoken term detection and forensic speaker identification.</p><br>
<p>LDC has released the following data sets in the CIEMPIESS series:</p><br>
<ul><br>
<li>CIEMPIESS (<a href="../../../LDC2015S07">LDC2015S07</a>)</li><br>
<li>CIEMPIESS Light (<a href="../../../LDC2017S23">LDC2017S23</a>)</li><br>
<li>CIEMPIESS Balance (<a href="../../../LDC2018S11">LDC2018S11</a>)</li><br>
<li>CIEMPIESS Experimentation (<a href="../../../LDC2019S07">LDC2019S07</a>)</li><br>
</ul><br>
<h3>Data</h3><br>
<p>This corpus is comprised of Mexican Spanish microphone speech from 75 male speakers and 75 female speakers in a quiet office environment. Speakers could answer pre-selected open questions or describe a particular painting shown to them on a computer monitor.</p><br>
<p>Speaker metadata in this release includes age, gender, place of birth, place of residence and parents' nationalities.</p><br>
<p>The audio files are presented as to 16 kHz, 16-bit PCM flac compressed wav.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2016S04.wav">audio sample</a> and <a href="desc/addenda/LDC2016S04.txt">text sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2012, 2016 Carlos Daniel Hernández Mena, © 2016 Trustees of the University of Pennsylvania
DOI: 10.35111/cvd6-rq48
title: H1 Children's Writing

description: <h3>Introduction</h3><br>
<p>H1 Children's Writing was developed by the <a href="http://www.dhbw.de/english/dhbw/about-us.html">Cooperative State University Baden-W&uuml;rttemberg</a>, <a href="http://www.ph-karlsruhe.de/index.php?id=5829">University of Education</a>. It consists of 996 texts written over three months by 88 German school children age seven through eleven years.</p><br>
<p>The data in this corpus was collected by an elementary school in Baden W&uuml;rttemberg, Germany and digitized at the Cooperative State University during the second half of the 2014/2015 school year. Three second and third grade classrooms participated in the collection.</p><br>
<p>Texts were written within regular class settings. The students were presented with a picture and were asked to write a story, to describe the picture or if unable to write a text, to list what they saw in the picture. The pictures were designed to enhance the output with respect to important spelling error categories, namely, the marking of short vowels with a silent consonant letter and the correct spelling of the long vowel. The children were allowed at least 15 minutes to write the texts. This exercise was repeated weekly for 12 weeks.</p><br>
<p>LDC has also released H2, E2, ERK1 Children's Writing (<a href="../../../LDC2018T05">LDC2018T05</a>).</p><br>
<h3>Data</h3><br>
<p>Most of the participants were multilingual. Out of 85 children for whom metadata is available, 57 students were multilingual speakers and 28 students were monolingual German speakers. The following metadata is included for each text in the database: school week of collection; school type (always elementary school); age; gender; grade/classroom; language spoken at home; and school materials used for German (Jojo).</p><br>
<p>In all, 996 texts representing 62,764 tokens were collected. The texts were digitized in two forms: (1) the original text, including all errors (achieved), and (2) the intended (target) text, where all spelling errors were removed. Annotations were added to both the achieved text and the target text to distinguish words that should not be analyzed for spelling errors, such as names or foreign words. For sentence-level analysis, syntax errors were annotated by marking substitutions, deletions and insertions at the word level. In such cases, the used word was analyzed for spelling, and the correct word was used for sentence structure analysis.</p><br>
<p>Original handwriting is presented as pdf documents and the converted text as UTF-8 plain text in csv documents.</p><br>
<h3>Samples</h3><br>
<p>Please view the following samples:</p><br>
<ul><br>
<li><a href="desc/addenda/LDC2016T01.pdf">Handwriting Sample</a></li><br>
<li><a href="desc/addenda/LDC2016T01.orig.txt">Original Transcription</a></li><br>
<li><a href="desc/addenda/LDC2016T01.corr.txt">Corrected Transcription</a></li><br>
</ul><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2016 Kay Berkling, Trustees of the University of Pennsylvania
DOI: 10.35111/q7nh-g640
title: Arabic Treebank - Weblog

description: <h3>Introduction</h3><br>
<p>Arabic Treebank - Weblog was developed by the Linguistic Data Consortium (LDC) and consists of Arabic weblog data with part-of-speech, morphology, gloss and syntactic tree annotation.</p><br>
<p>The ongoing Penn Arabic Treebank Project (PATB) supports research in Arabic-language natural language processing and human language technology development. The methodology and work leading to the release of this publication are described in detail in the documentation accompanying this corpus. Generally, the PATB consists of two distinct phases: (a) part-of-speech (POS) tagging, which divides the text into lexical tokens and gives relevant information about each token such as lexical category, inflectional features, and a gloss (referred to as POS for convenience, although it includes morphological and gloss information not traditionally included with part-of-speech annotation), and (b) Arabic treebanking, which characterizes the constituent structures of word sequences, provides categories for each non-terminal node, and identifies null elements, co-reference, traces and so on.</p><br>
<h3>Data</h3><br>
<p>This release contains 243,117 source tokens before clitics were split, and 308,996 tree tokens after clitics were separated for treebank annotation. The source material is weblogs collected by LDC from various sources.</p><br>
<p>The data are released as plain-text, tdf and xml files in UTF-8.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2016T02.jpg">sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p><br>
<h3>Acknowledgement</h3><br>
<p>This work was supported in part by the Defense Advanced Research Projects Agency, GALE Program Grant No. HR0011-06-1-0003. The content of this publication does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.</p></br>
Portions © 2016 Trustees of the University of Pennsylvania
DOI: 10.35111/60j1-yd62
title: NewSoMe Corpus of Opinion in Blogs

description: <h3>Introduction</h3><br>
<p>NewSoMe Corpus of Opinion in Blogs was compiled at <a href="http://www.barcelonamedia.org/">Barcelona Media</a> and consists of English and Spanish blogs annotated for opinions. It is part of the NewSoMe (News and Social Media) set of corpora presenting opinion annotations across several genres and covering multiple languages. NewSoMe is the result of an effort to build a unifying annotation framework for analyzing opinion in different genres, ranging from controlled text, such as news reports, to diverse types of user-generated content that includes blogs, product reviews and microblogs.</p><br>
<p>LDC has also released NewSoMe Corpus of Opinion in News Reports (<a href="../../../LDC2015T17">LDC2015T17</a>).</p><br>
<h3>Data</h3><br>
<p>The source data in this corpus was obtained by means of the <a href="https://developers.google.com/blog-search/">Google Blog Search API</a>. Spanish blogs were taken from <a href="http://wordpress.com">wordpress.com</a> and <a href="http://blogspot.com">blogspot.com</a> blogs. The English data was extracted from those same two domains and from <a href="http://asiawrites.org">asiawrites.org</a>.</p><br>
<p>This release consists of 108 English documents and 191 Spanish documents. The annotation was carried out manually through the crowdsourcing platform <a href="http://www.crowdflower.com/">CrowdFlower</a> with seven annotations per layer that were aggregated for this data set. The layers annotated were topic, segment, cue, subjectivity, polarity and intensity.</p><br>
<p>Data is presented as UTF-8 either as plain text or in CSV files.</p><br>
<h3>Samples</h3><br>
<p>Please view thiese samples:</p><br>
<ul><br>
<li><a href="desc/addenda/LDC2016T03.sp.txt">Spanish Raw</a></li><br>
<li><a href="desc/addenda/LDC2016T03.en.topic.csv">English Topics</a></li><br>
<li><a href="desc/addenda/LDC2016T03.sp.sent.csv">Spnish Sentences</a></li><br>
</ul><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2016 Fundacio Barcelona Media, © 2016 Trustees of the University of Pennsylvania