“Context Resolution” Task in NLPOpenNLP Coreference Resolution (German)Coreference Resolution for German TextsExtract sentences from beginning of news in single document summarizationClassify sentences containing typos into groupsNeed help/direction in an NLP Task ( Question Answering ) ModelText extraction from documents using NLP or Deep LearningSkip-thought models applied to phrases instead of sentencesHow to detect when the “bibliography” of a paper has began?Word classification (not text classification) using NLPWhat is the motivation for row-wise convolution and folding in Kalchbrenner et al. (2014)?
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“Context Resolution” Task in NLP
OpenNLP Coreference Resolution (German)Coreference Resolution for German TextsExtract sentences from beginning of news in single document summarizationClassify sentences containing typos into groupsNeed help/direction in an NLP Task ( Question Answering ) ModelText extraction from documents using NLP or Deep LearningSkip-thought models applied to phrases instead of sentencesHow to detect when the “bibliography” of a paper has began?Word classification (not text classification) using NLPWhat is the motivation for row-wise convolution and folding in Kalchbrenner et al. (2014)?
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I'm looking for references to a standard(-ish) task/dataset in NLP that is close(-ish) to the following: we have a document with a list of references (sorry), for example, a scientific paper. For every reference, we have a sentence within the document and the corresponding text of another paper. The task is to find sentences/regions within the corresponding text, that "support" the sentence in the original text, given some metric. Basically, what anyone would do given cumbersome unexplained statement within some mind-boggling paper.
Apart from the main question, what are the possible/good/standard metrics one can use? Are there remarkable implementations/users of some in-house solutions/any other useful remarks?
nlp
asked 9 hours ago
Michael DudalevMichael Dudalev
62
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Michael Dudalev is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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$endgroup$
add a comment |
$begingroup$
I'm looking for references to a standard(-ish) task/dataset in NLP that is close(-ish) to the following: we have a document with a list of references (sorry), for example, a scientific paper. For every reference, we have a sentence within the document and the corresponding text of another paper. The task is to find sentences/regions within the corresponding text, that "support" the sentence in the original text, given some metric. Basically, what anyone would do given cumbersome unexplained statement within some mind-boggling paper.
Apart from the main question, what are the possible/good/standard metrics one can use? Are there remarkable implementations/users of some in-house solutions/any other useful remarks?
nlp
asked 9 hours ago
Michael DudalevMichael Dudalev
62
New contributor
Michael Dudalev is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I'm looking for references to a standard(-ish) task/dataset in NLP that is close(-ish) to the following: we have a document with a list of references (sorry), for example, a scientific paper. For every reference, we have a sentence within the document and the corresponding text of another paper. The task is to find sentences/regions within the corresponding text, that "support" the sentence in the original text, given some metric. Basically, what anyone would do given cumbersome unexplained statement within some mind-boggling paper.
Apart from the main question, what are the possible/good/standard metrics one can use? Are there remarkable implementations/users of some in-house solutions/any other useful remarks?
nlp
asked 9 hours ago
Michael DudalevMichael Dudalev
62
New contributor
Michael Dudalev is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I'm looking for references to a standard(-ish) task/dataset in NLP that is close(-ish) to the following: we have a document with a list of references (sorry), for example, a scientific paper. For every reference, we have a sentence within the document and the corresponding text of another paper. The task is to find sentences/regions within the corresponding text, that "support" the sentence in the original text, given some metric. Basically, what anyone would do given cumbersome unexplained statement within some mind-boggling paper.
Apart from the main question, what are the possible/good/standard metrics one can use? Are there remarkable implementations/users of some in-house solutions/any other useful remarks?
nlp
nlp
asked 9 hours ago
Michael DudalevMichael Dudalev
62
New contributor
Michael Dudalev is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 9 hours ago
Michael DudalevMichael Dudalev
62
New contributor
Michael Dudalev is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 9 hours ago
Michael DudalevMichael Dudalev
62
New contributor
Michael Dudalev is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 9 hours ago
Michael DudalevMichael Dudalev
62
asked 9 hours ago
Michael DudalevMichael Dudalev
62
62
New contributor
Michael Dudalev is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Michael Dudalev is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Michael Dudalev is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
add a comment |
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