31 to 40 of 52 Results
Sep 5, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Wiegand, Michael; Ruppenhofer, Josef; Schulder, Marc, 2019, "Sentiment View Lexicon (EN)", https://doi.org/10.11588/data/2JK48O, heiDATA, V1
This gold standard contains sentiment expressions (verbs, nouns and adjectives) that have been annotated according to their (prior) sentiment view. Each sentiment expression is labelled either as actor or speaker view. |
Sep 5, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Wiegand, Michael; Bocionek, Christine; Ruppenhofer, Josef, 2019, "Sentiment Compound Data (DE)", https://doi.org/10.11588/data/LSTRK3, heiDATA, V1
This dataset contains gold standards that are required for building a classifier that automatically extracts opinion (noun) compounds. |
Sep 9, 2019 - AWI Experimental Economics
Nikiforakis, Nikos; Oechssler, Jörg; Shah, Anvar, 2019, "Managerial bonuses and subordinate mistreatment [Dataset]", https://doi.org/10.11588/data/876SOV, heiDATA, V1, UNF:6:rgdksaMzfE0dDvw+toLLbg== [fileUNF]
Can performance bonuses increase the likelihood that managers coerce their subordinates into exerting high levels of effort when doing so promotes neither efficiency nor equity? We consider a laboratory setting in which managers compete to obtain a large bonus at the end of the e... |
Sep 27, 2019 - Medical Informatics
Seitz, Max W.; Listl, Stefan; Bartols, Andreas; Schubert, Ingrid; Blaschke, Katja; Haux, Christian; van der Zande, Marieke M., 2019, "Current knowledge on correlations between highly prevalent dental conditions and chronic diseases: an umbrella review [Dataset]", https://doi.org/10.11588/data/ORTPJN, heiDATA, V1
Introduction: There are existing studies investigating relationships between chronic systemic and dental conditions, but it remains unclear how such knowledge can be used in clinical practice. The present report provides an overview on existing systematic reviews, identifying and... |
Sep 30, 2019 - AWI Experimental Economics
Schmidt, Robert, 2019, "Norms in the Lab: Inexperienced versus Experienced Participants", https://doi.org/10.11588/data/SS8CBF, heiDATA, V2, UNF:6:4c/ba9USuo/U6JX/7Gh1Mw== [fileUNF]
Using coordination games, we study whether social norm perception differs between inexperienced and experienced participants in economic laboratory experiments. We find substantial differences between the two groups, both regarding injunctive and descriptive social norms in the c... |
Oct 7, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Marasović, Ana, 2019, "Multilingual Modal Sense Classification using a Convolutional Neural Network [Source Code]", https://doi.org/10.11588/data/ERDJDI, heiDATA, V1
Abstract Modal sense classification (MSC) is aspecial WSD task that depends on themeaning of the proposition in the modal’s scope. We explore a CNN architecture for classifying modal sense in English and German. We show that CNNs are superior to manually designed feature-based cl... |
Oct 7, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Marasović, Ana; Zhou, Mengfei; Frank, Anette, 2019, "The MSC Data Set", https://doi.org/10.11588/data/JEESIQ, heiDATA, V1
From this page you can download resources we created for modal sense classification as reported in Zhou et al. (2015), Marasović et al. (2016) and Marasović and Frank (2015) (see "Related Publication" below): Heuristically sense-annotated training data acquired from EUROPARL and... |
Oct 8, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Ruppenhofer, Josef, 2019, "Affixoid Dataset (DE)", https://doi.org/10.11588/data/QKF4LT, heiDATA, V1, UNF:6:+MGK9lTPTXx7Rclu1BpPnw== [fileUNF]
The dataset contains the manual annotations for the COLING 2018 submission "Distinguishing affixoid formations from compounds" by Josef Ruppenhofer, Michael Wiegand, Rebecca Wilm and Katja Markert. 1788 complex words containing one of 7 German suffixoid candidates (e.g. -hai, -go... |
Oct 22, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Becker, Maria, 2019, "COREC – A neural multi-label COmmonsense RElation Classification system", https://doi.org/10.11588/data/E5EHBV, heiDATA, V1
We examine the learnability of Commonsense knowledge relations as represented in CONCEPTNET. We develop a neural open world multi-label classification system that focuses on the evaluation of classification accuracy for individual relations. Based on an in-depth study of the spec... |
Oct 22, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Becker, Maria, 2019, "Genre-sensitive Neural Situation Entity classifier (DE, EN)", https://doi.org/10.11588/data/XXKWU0, heiDATA, V1
This is a Classifier for situation entity types as described in Becker et al., 2017. These clause types depend on a combination of syntactic-semantic and contextual features. We explore this task in a deeplearning framework, where tuned word representations capture lexical, synta... |