The MSC Data Set
收藏资源简介:
<p>From this page you can download resources we created for <strong>modal sense classification</strong> as reported in Zhou et al. (2015), Marasović et al. (2016) and Marasović and Frank (2015) (see "Related Publication" below):</p> <ul> <li>Heuristically sense-annotated training data acquired from EUROPARL and OpenSubtitles (<strong>EPOS_E</strong>, English). The dataset was used for: <ul> <li>the EMNLP 2015 Workshop submission "Semantically enriched models for modal sense classification" by Mengfei Zhou, Anette Frank,Annemarie Friedrich, and Alexis Palmer</li> <li>the LiLT submission "Modal Sense Classification At Large: Paraphrase-Driven Sense Projection, Semantically Enriched Classification Models and Cross-Genre Evaluations" by Ana Marasović, Mengfei Zou, Alexis Palmer, Anette Frank</li> <li>the RepL4NLP submission "Multilingual Modal Sense Classification using a Convolutional Neural Network" by Ana Marasović and Anette Frank.</li> </ul> </li> <li>Composition of training and testing used for the classification experiments. The dataset was used for: <ul> <li>the EMNLP 2015 Workshop submission "Semantically enriched models for modal sense classification" by submission Mengfei Zhou, Anette Frank,Annemarie Friedrich, and Alexis Palmer</li> <li>the RepL4NLP submission "Multilingual Modal Sense Classification using a Convolutional Neural Network" by Ana Marasović and Anette Frank.</li> </ul> </li> <li>Manually annotated subsection of <strong>MASC</strong> (English). The dataset was used for the LiLT submission "Modal Sense Classification At Large: Paraphrase-Driven Sense Projection, Semantically Enriched Classification Models and Cross-Genre Evaluations" by Ana Marasović, Mengfei Zou, Alexis Palmer, Anette Frank.</li> <li>Heuristically modal sense annotated training data and manually annotated test data from EUROPARL and OpenSubtitles (<strong>EPOS_G</strong>, German). The dataset was used for the RepL4NLP submission "Multilingual Modal Sense Classification using a Convolutional Neural Network" by Ana Marasović and Anette Frank.</li> </ul> <p>&nbsp;</p>



