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dc.contributor.authorSchiller, Benjamin
dc.contributor.authorGurevych, Iryna
dc.contributor.authorDaxenberger, Johannes
dc.date.accessioned2020-05-07T16:47:03Z
dc.date.available2020-05-07T16:47:03Z
dc.date.issued2020-05
dc.identifier.urihttps://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2329
dc.descriptionThis collection holds (1) the argument aspect detection corpus, (2) the data to reproduce the training of the language models described in the paper, and (3) the arguments generated with both language models. The argument aspect detection corpus includes 5,032 arguments over eight controversial topics, annotated with aspects by crowdworkers. DISCLAIMER: All material provided in the archives reddit_training_data.7z and cc_training_data.7z may be used for research purposes only. For all other material in this collection (namely argument_aspect_detection_v1.0.7z and generated_arguments.7z), this restriction does not apply. The user acknowledges and agrees that the data is provided on an “as­-is” basis and that the licensor makes no representations or warranties of any kind.en_US
dc.language.isoenen_US
dc.relationIsCitedBy;arXiv;2005.00084
dc.rightsIn Copyright
dc.rights.urihttps://rightsstatements.org/vocab/InC/1.0/
dc.subjectargument generationen_US
dc.subjectaspect detectionen_US
dc.subjectcontrolled argument generationen_US
dc.titleTraining Data for Aspect-Controlled Neural Argument Generation en_US
dc.typeDataseten_US
dc.description.version1.0en_US
tud.projectDFG | GU798/25-1 | Offenes Argument-Minen_US
tud.projectPTJ | 03VP02540 | ArgumenTexten_US


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Except where otherwise noted, this item's license is described as In Copyright