cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35111/me9d-jr38
title: BOLT Egyptian-English Word Alignment -- Discussion Forum Training

description: <h3>Introduction</h3><br>
<p>BOLT Egyptian-English Word Alignment -- Discussion Forum Training was developed by the Linguistic Data Consortium (LDC) and consists of 400,448 words of Egyptian Arabic and English parallel text enhanced with linguistic tags to indicate word relations.</p><br>
<p>The DARPA <a href="https://www.ldc.upenn.edu/collaborations/current-projects/bolt">BOLT</a> (Broad Operational Language Translation) program developed machine translation and information retrieval for less formal genres, focusing particularly on user-generated content. LDC supported the BOLT program by collecting informal data sources -- discussion forums, text messaging and chat -- in Chinese, Egyptian Arabic and English. The collected data was translated and annotated for various tasks including word alignment, treebanking, propbanking and co-reference.</p><br>
<h3>Data</h3><br>
<p>This release consists of Egyptian source discussion forum threads harvested from the Internet by LDC using a combination of manual and automatic processes. The source data is released as BOLT Arabic Discussion Forums (<a href="../../../LDC2018T10">LDC2018T10</a>).</p><br>
<p>The BOLT word alignment task was built on treebank annotation. Specifically, Egyptian source tree tokens for word alignment were automatically extracted from tree files of BOLT Egyptian Arabic Treebank annotation on the source discussion forum data harvested by LDC. Human annotators then followed LDC guidelines to link words and phrases in Arabic to those in English.</p><br>
<p>The data profile broken down by character tokens, tree tokens and segments appears below:</p><br>
<table border="1" cellpadding="5"><br>
<tbody><br>
<tr><br>
<td>Language</td><br>
<td>Genre</td><br>
<td>Files</td><br>
<td>Words</td><br>
<td>Tree-tokens</td><br>
<td>Segments</td><br>
</tr><br>
<tr><br>
<td>Egyptian Arabic</td><br>
<td>discussion forum</td><br>
<td>724</td><br>
<td>400,448</td><br>
<td>593,723</td><br>
<td>31,454</td><br>
</tr><br>
</tbody><br>
</table><br>
<h3>Acknowledgement</h3><br>
<p>This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR0011-11-C-0145. The content 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/LDC2019T06.arz.tkn">Egyptian Tokenized</a></li><br>
<li><a href="desc/addenda/LDC2019T06.eng.tkn">English Tokenized</a></li><br>
<li><a href="desc/addenda/LDC2019T06.wa">Word Alignment</a></li><br>
</ul><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2012-2015, 2018, 2019 Trustees of the University of Pennsylvania
DOI: 10.35111/8ddt-ze77
title: Chinese Abstract Meaning Representation 1.0

description: <h3>Introduction</h3><br>
<p>Chinese Abstract Meaning Representation was developed by <a href="https://www.brandeis.edu/">Brandeis University</a> and <a href="http://en.njnu.edu.cn/">Nanjing Normal University</a> and is comprised of semantic representations of a set of Chinese sentences from Chinese Treebank 8.0 (<a href="../../../LDC2013T21">LDC2013T21</a>).</p><br>
<p>Abstract Meaning Representation (AMR) captures "who is doing what to whom" in a sentence. Each sentence is paired with a graph that represents its whole-sentence meaning in a tree structure. LDC has released the following AMR English data sets: Abstract Meaning Representation (AMR) Annotation Release 1.0 (<a href="../../../LDC2014T12">LDC2014T12</a>) and Abstract Meaning Representation (AMR) Annotation Release 2.0 (<a href="../../../LDC2017T10">LDC2017T10</a>).</p><br>
<p>Chinese AMR is based on the annotation methodology developed for English with adaptations for handling specific Chinese phenomena. The goal of the Chinese AMR project is to create a large aligned AMR corpus, of which this data set is the first release. For more information about the project, see the <a href="http://www.cs.brandeis.edu/~clp/camr/camr.html">Chinese AMR homepage</a>.</p><br>
<h3>Data</h3><br>
<p>The text is extracted from the 10,325 sentences of the weblog and discussion forum portions of Chinese Treebank 8.0. Annotations were applied to 10,149 sentences, with 176 sentences unannotated.</p><br>
<p>The data is divided into training, development and test sets. These three files are presented as plain text in UTF-8 encoding.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2019T07.txt">sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2019 Bin Li, © 2001, 2004, 2005, 2007, 2009, 2010, 2013, 2019 Trustees of the University of Pennsylvania
DOI: 10.35111/69fx-s086
title: DEFT Spanish Committed Belief Annotation

description: <h3>Introduction</h3><br>
<p>DEFT Spanish Committed Belief Annotation was developed by the Linguistic Data Consortium (LDC) and consists of approximately 67,000 tokens of Spanish discussion forum text annotated for "committed belief," which marks the level of commitment displayed by the author to the truth of the propositions expressed in the text.</p><br>
<p>DARPA's Deep Exploration and Filtering of Text (DEFT) program aimed to address remaining capability gaps in state-of-the-art natural language processing technologies related to inference, causal relationships and anomaly detection. LDC supported the DEFT program by collecting, creating and annotating a variety of data sources.</p><br>
<p>LDC has also released DEFT Chinese Committed Belief Annotation (<a href="../../../LDC2019T03">LDC2019T03</a>).</p><br>
<h3>Data</h3><br>
<p>The source data is Spanish discussion forum web text collected by LDC. Annotations fall into one of four categories: committed belief, non-committed belief, reported belief and not applicable. Further information about the annotation methodology is contained in the documentation accompanying this release.</p><br>
<p>This publication contains 87 files (67,395 tokens). Annotation files are stored in XML format, and source documents are stored in plain text format. Both types of files are encoded in UTF-8.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2019T09.src.txt">source sample</a> and <a href="desc/addenda/LDC2019T09.xml">annotation sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p><br>
<h3>Acknowledgement</h3><br>
<p>This material is based on research sponsored by Air Force Research Laboratory and Defense Advance Research Projects Agency under agreement number FA8750-13-2-0045. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Air Force Research Laboratory and Defense Advanced Research Projects Agency or the U.S. Government.</p></br>
Portions © 2019 Trustees of the University of Pennsylvania
DOI: 10.35111/qxep-jt47
title: Corpus of Conversational Persian Transcripts

description: <h3>Introduction</h3><br>
<p>Corpus of Conversational Persian Transcripts consists of transcripts from approximately 20 hours of naturally occurring informal conversations in the Tehrani dialect of Iranian Persian. The corresponding speech is not included in this release.</p><br>
<h3>Data</h3><br>
<p>This corpus is extracted from 1,201 minutes of conversations among 22 participants, 12 male and 10 female. The participants recorded their daily phone calls and face-to-face interactions in a variety of informal settings. The conversations represent various interaction types, settings, types of relationship, and communicative goals.</p><br>
<p>The transcripts were annotated for gender, age, and recording method and setting. See the included documentation for more information about the annotations and transcription methodology.</p><br>
<p>Each conversation is presented as a UTF-8 encoded XML file.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2019T11.xml">sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2019 Ariana N. Mohammadi, © 2019 Trustees of the University of Pennsylvania
DOI: 10.35111/bwg4-0h19
title: TAC KBP Evaluation Source Corpora 2016-2017

description: <h3>Introduction</h3><br>
<p>TAC KBP Evaluation Source Corpora 2016-2017 was developed by the Linguistic Data Consortium (LDC) and contains the 180,003 Chinese, English and Spanish source documents used in support of all TAC KBP evaluation tracks conducted in <a href="https://tac.nist.gov/2016/KBP/index.html">2016</a> and <a href="https://tac.nist.gov/2017/index.html">2017</a>.</p><br>
<p>Text Analysis Conference (<a href="https://tac.nist.gov/">TAC</a>) is a series of workshops organized by the National Institute of Standards and Technology (<a href="https://www.nist.gov/">NIST</a>). TAC was developed to encourage research in natural language processing and related applications by providing a large test collection, common evaluation procedures, and a forum for researchers to share their results. Through its various evaluations, the Knowledge Base Population (KBP) track of TAC encourages the development of systems that can match entities mentioned in natural texts with those appearing in a knowledge base and extract novel information about entities from a document collection and add it to a new or existing knowledge base.</p><br>
<h3>Data</h3><br>
<p>The source data consists of Chinese, English and Spanish discussion forum and newswire text collected by LDC. Documents are released as UTF-8 encoded XML with corresponding DTDs. Also provided are a series of lists and tables to aid in the recreation of specific test sets. See the included documentation for more information.</p><br>
<h3>Acknowledgement</h3><br>
<p>This material is based on research sponsored by Air Force Research Laboratory and Defense Advance Research Projects Agency under agreement number FA8750-13-2-0045. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Air Force Research Laboratory and Defense Advanced Research Projects Agency or the U.S. Government.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2019T12.xml">sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2013 New York Times, © 2013 Xinhua News Agency, © 2013, 2018, 2019 Trustees of the University of Pennsylvania
DOI: 10.5517/ccdc.csd.cc2796j9
title: CCDC 2064430: Experimental Crystal Structure Determination

description: Related Article: Yubiao Hong,  Tianjiao Cui,  Sergei Ivlev,  Xiulan Xie,  Eric Meggers|2021|Chem.-Eur.J.|27|8557|doi:10.1002/chem.202100703
DOI: 10.35111/8pye-2w87
title: Machine Reading Phase 1 NFL Scoring Training Data

description: <h3>Introduction</h3><br>
<p>Machine Reading Phase 1 NFL Scoring Training Data was developed by the Linguistic Data Consortium (LDC) and contains 110 US NFL (National Football League) scoring source documents and 110 standoff annotation files used in the DARPA (Defense Advanced Research Projects Agency) Machine Reading program.</p><br>
<p>The Machine Reading program aimed to develop automated reading systems to bridge the gap between knowledge contained in natural language texts and knowledge accessible to formal reasoning systems. The reading systems designed by program participants were required to extract and reason about facts from text in multiple domains.</p><br>
<p>The data in this release constitutes the training data for the NFL Scoring Use Cases evaluation. The NFL Scoring Use Cases tested the sports domain by extracting information about scoring events and outcomes of US NFL games and by aligning that information with an NFL Scoring ontology.</p><br>
<h3>Data</h3><br>
<p>This release contains 110 source documents (70,233 words) from English newswire stories. The files were manually annotated for instances of NFL Scoring annotation categories defined with respect to the NFL Scoring ontology.</p><br>
<p>Annotations are in GUI XML (traditional annotation) and RDF XML (formal knowledge representation) formats. All source and annotation files are presented as UTF-8 encoded XML files with associated dtds.</p><br>
<h3>Acknowledgments</h3><br>
<p>The Linguistic Data Consortium gratefully acknowledges the support of Defense Advanced Research Projects Agency (DARPA) Machine Reading Program under Air Force Research Laboratory (AFRL) prime contract no. FA8750-09 C-xxxx. Any opinions, findings, and conclusion or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the view of the DARPA, AFRL, or the US government.</p><br>
<h3>Samples</h3><br>
<p>Please view the following samples:</p><br>
<ul><br>
<li><a href="desc/addenda/LDC2019T14.src.xml">Source Sample</a></li><br>
<li><a href="desc/addenda/LDC2019T14.gui.xml">GUI XML Sample</a></li><br>
<li><a href="desc/addenda/LDC2019T14.rdf.xml">RDF XML Sample</a></li><br>
</ul><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 1995-1996, 2002-2005 Agence France Presse, ©1998, 2000-2001 The Associated Press, © 1994, 1996, 1998, 2005 New York Times, © 2003, 2005, 2007, 2009, 2011, 2019 Trustees of the University of Pennsylvania
DOI: 10.35111/xpnt-sz28
title: BOLT English Treebank - Discussion Forum

description: <h3>Introduction</h3><br>
<p>BOLT English Treebank - Discussion Forum was developed by the Linguistic Data Consortium (LDC) and consists of English web discussion forum data with part-of-speech and syntactic structure annotations.</p><br>
<p>The DARPA <a href="https://www.ldc.upenn.edu/collaborations/current-projects/bolt">BOLT</a> (Broad Operational Language Translation) program developed machine translation and information retrieval for less formal genres, focusing particularly on user-generated content. LDC supported the BOLT program by collecting informal data sources -- discussion forums, text messaging and chat -- in Chinese, Egyptian Arabic and English. The collected data was translated and annotated for various tasks including word alignment, treebanking, propbanking and co-reference.</p><br>
<p>The unannotated English source data is released as BOLT English Discussion Forums (<a href="../../../LDC2017T11">LDC2017T11</a>).</p><br>
<p>Part-of-speech and treebank annotation conformed to Penn Treebank II style, incorporating changes to those guidelines that were developed under the GALE (Global Autonomous Language Exploitation) program. Those changes primarily concerned the tokenization of hyphenated words, part-of-speech and tree changes necessitated by the tokenization changes, and updates to the syntactic annotation to comply with updated annotation guidelines. Supplementary guidelines for English treebanks and web text are included with this release.</p><br>
<h3>Data</h3><br>
<p>The source data is English discussion forum web text collected by LDC in 2011 and 2012. A subset of that collection -- 702 files representing 268,907 tokens -- was selected for the treebank and annotated for word-level tokenization, part-of-speech and syntactic structure.</p><br>
<p>Data is presented in a a variety of UTF-8 encoded text formats, specifically, plain text, XML, and Penn Treebank. See the included documentation for more information about specific formats.</p><br>
<h3>Acknowledgement</h3><br>
<p>This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR0011-11-C-0145. The content 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/LDC2019T15.eng.su.xml.src.flat.txt">Source</a></li><br>
<li><a href="desc/addenda/LDC2019T15.xml.tree.txt">Penn Treebank</a></li><br>
<li><a href="desc/addenda/LDC2019T15.xml">XML</a></li><br>
</ul><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2011-2019 Trustees of the University of Pennsylvania
DOI: 10.5517/ccdc.csd.cc2796kb
title: CCDC 2064431: Experimental Crystal Structure Determination

description: Related Article: Yubiao Hong,  Tianjiao Cui,  Sergei Ivlev,  Xiulan Xie,  Eric Meggers|2021|Chem.-Eur.J.|27|8557|doi:10.1002/chem.202100703
DOI: 10.35111/830w-pf92
title: DEFT English Committed Belief Annotation

description: <h3>Introduction</h3><br>
<p>DEFT English Committed Belief Annotation was developed by the Linguistic Data Consortium (LDC) and consists of approximately 950,000 words of English discussion forum text annotated for "committed belief," which marks the level of commitment displayed by the author to the truth of the propositions expressed in the text.</p><br>
<p>DARPA's Deep Exploration and Filtering of Text (DEFT) program aimed to address remaining capability gaps in state-of-the-art natural language processing technologies related to inference, causal relationships and anomaly detection. LDC supported the DEFT program by collecting, creating and annotating a variety of data sources.</p><br>
<p>LDC has also released DEFT Chinese Committed Belief Annotation (<a href="../../../LDC2019T03">LDC2019T03</a>) and DEFT Spanish Committed Belief Annotation (<a href="../../../LDC2019T09">LDC2019T09</a>).</p><br>
<h3>Data</h3><br>
<p>The source data is English discussion forum web text collected by LDC. Annotations fall into one of four categories: committed belief, non-committed belief, reported belief and not applicable. Further information about the annotation methodology is contained in the documentation accompanying this release.</p><br>
<p>This publication contains 1,217 files (952,723 words). Annotation files are stored in XML format, and source documents are stored in plain text format. Both types of files are encoded in UTF-8.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2019T16.txt">source sample</a> and <a href="desc/addenda/LDC2019T16.xml">annotation sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p><br>
<h3>Acknowledgement</h3><br>
<p>This material is based on research sponsored by Air Force Research Laboratory and Defense Advance Research Projects Agency under agreement number FA8750-13-2-0045. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Air Force Research Laboratory and Defense Advanced Research Projects Agency or the U.S. Government.</p></br>
Portions © 2019 Trustees of the University of Pennsylvania
DOI: 10.35111/1kea-zq24
title: BOLT Egyptian Arabic-English Word Alignment -- SMS/Chat Training

description: <h3>Introduction</h3><br>
<p>BOLT Egyptian Arabic-English Word Alignment -- SMS/Chat Training was developed by the Linguistic Data Consortium (LDC) and consists of 349,414 words of Egyptian Arabic and English parallel text enhanced with linguistic tags to indicate word relations.</p><br>
<p>The DARPA <a href="https://www.ldc.upenn.edu/collaborations/current-projects/bolt">BOLT</a> (Broad Operational Language Translation) program developed machine translation and information retrieval for less formal genres, focusing particularly on user-generated content. LDC supported the BOLT program by collecting informal data sources -- discussion forums, text messaging and chat -- in Chinese, Egyptian Arabic and English. The collected data was translated and annotated for various tasks including word alignment, treebanking, propbanking and co-reference.</p><br>
<h3>Data</h3><br>
<p>This release consists of Egyptian Arabic source text message and chat conversations collected using two methods: new collection via LDC's collection platform, and donation of SMS or chat archives from BOLT collection participants. The source data is released as BOLT Egyptian Arabic SMS/Chat and Transliteration (<a href="../../../LDC2017T07">LDC2017T07</a>).</p><br>
<p>The BOLT word alignment task was built on treebank annotation. Specifically, Egyptian Arabic source tree tokens were automatically extracted from tree files in LDC's BOLT Egyptian Arabic Treebank. Those tree files had been tagged for part-of-speech and syntactically annotated. That data was then aligned and annotated for the word alignment task.</p><br>
<p>The data profile broken down by character tokens, tree tokens and segments appears below:</p><br>
<table border="1" cellpadding="5"><br>
<tbody><br>
<tr><br>
<td>Language</td><br>
<td>Genre</td><br>
<td>Files</td><br>
<td>Words</td><br>
<td>Tree/POS-tokens</td><br>
<td>Segments</td><br>
</tr><br>
<tr><br>
<td>Egyptian Arabic</td><br>
<td>SMS/Chat</td><br>
<td>1367</td><br>
<td>349,414</td><br>
<td>475,665</td><br>
<td>74,814</td><br>
</tr><br>
</tbody><br>
</table><br>
<h3>Acknowledgement</h3><br>
<p>This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR0011-11-C-0145. The content 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/LDC2019T18.arz.tkn.txt">Egyptian Arabic Source</a></li><br>
<li><a href="desc/addenda/LDC2019T18.eng.tkn.txt">English Translation</a></li><br>
<li><a href="desc/addenda/LDC2019T18.wa.txt">Word Alignment</a></li><br>
</ul><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
 Portions © 2019 Trustees of the University of Pennsylvania
DOI: 10.6073/pasta/4a25e48ffca38df7d2a0c4dd503be54b
title: Soil Invertebrate Species in Macrosystems Biodiversity Project at Harvard Forest 2012

description: Leaf litter invertebrates and soil microbes were sampled in an array of 21 1m2 subplots by the Kaspari Ant Lab at the University of Oklahoma as part of a macrosystems biodiversity and latitude project supported by the National Science Foundation under Cooperative Agreement DEB#1065836.