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Subject: Computer and Information Science

51 to 60 of 84 Results

German causal language annotations and lexicon (verbs, nouns, prepositions) (DE) Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo) Rehbein, Ines; Ruppenhofer, Josef, 2020, "German causal language annotations and lexicon (verbs, nouns, prepositions) (DE)", https://doi.org/10.11588/data/ZHI94V, heiDATA, V1 Annotations of causal verbs, nouns and prepositions in context and lexicon file for causal verbs, nouns and prepositions.
Encoder-Decoder Model for Semantic Role Labeling Jan 23, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo) Daza, Angel, 2020, "Encoder-Decoder Model for Semantic Role Labeling", https://doi.org/10.11588/data/TOI9NQ, heiDATA, V1 Abstract (Daza & Frank 2019): We propose a Cross-lingual Encoder-Decoder model that simultaneously translates and generates sentences with Semantic Role Labeling annotations in a resource-poor target language. Unlike annotation projection techniques, our model does not need paral...
3D Micro-Mapping of Subsidence Stations [Source Code and Data] Jan 15, 2020 - 3D Spatial Data Processing Herfort, Benjamin; Anders, Katharina; Marx, Sabrina; Eberlein, Stefan; Höfle, Bernhard, 2020, "3D Micro-Mapping of Subsidence Stations [Source Code and Data]", https://doi.org/10.11588/data/OU8YA1, heiDATA, V1 This dataset comprises the source code to reproduce the 3D micro-mapping tool for plane adjustment at subsidence stations. In this project, users adjust a plane (height and orientation) at the positions of fixed poles, so-called subsidence stations, to provide information on the...
Sensor-Based Measurements in Paraplegia: Classified References from a Systematic Review Jan 4, 2020 - Medical Informatics Benning, Nils-Hendrik; Hagen, Niclas; Knaup, Petra, 2020, "Sensor-Based Measurements in Paraplegia: Classified References from a Systematic Review", https://doi.org/10.11588/data/JRVJGN, heiDATA, V1, UNF:6:f63Fk7qwB3+Tc3vOEqFdnA== [fileUNF] This dataset contains the results (publication references) of the systematic review "Current Use of Sensor-Based Measurements for Paraplegics", presented at MIE 2020, Geneva.
GER_SET: Situation Entity Type labelled corpus for German Dec 10, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo) Becker, Maria, 2019, "GER_SET: Situation Entity Type labelled corpus for German", https://doi.org/10.11588/data/BBQYD0, heiDATA, V1 Semantic clause types, also called Situation Entity (SE) types (Smith, 2003) are linguistic characterizations of aspectual properties shown to be useful for tasks like argumentation structure analysis (Becker et al., 2016), genre characterization (Palmer and Friedrich, 2014), and...
Genre-sensitive Neural Situation Entity classifier (DE, EN) 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...
COREC – A neural multi-label COmmonsense RElation Classification system 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...
Affixoid Dataset (DE) 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...
The MSC Data Set 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...
Multilingual Modal Sense Classification using a Convolutional Neural Network [Source Code] 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...

German causal language annotations and lexicon (verbs, nouns, prepositions) (DE)

Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)

Rehbein, Ines; Ruppenhofer, Josef, 2020, "German causal language annotations and lexicon (verbs, nouns, prepositions) (DE)", https://doi.org/10.11588/data/ZHI94V, heiDATA, V1

Annotations of causal verbs, nouns and prepositions in context and lexicon file for causal verbs, nouns and prepositions.

Encoder-Decoder Model for Semantic Role Labeling

Jan 23, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)

Daza, Angel, 2020, "Encoder-Decoder Model for Semantic Role Labeling", https://doi.org/10.11588/data/TOI9NQ, heiDATA, V1

Abstract (Daza & Frank 2019): We propose a Cross-lingual Encoder-Decoder model that simultaneously translates and generates sentences with Semantic Role Labeling annotations in a resource-poor target language. Unlike annotation projection techniques, our model does not need paral...

3D Micro-Mapping of Subsidence Stations [Source Code and Data]

Jan 15, 2020 - 3D Spatial Data Processing

Herfort, Benjamin; Anders, Katharina; Marx, Sabrina; Eberlein, Stefan; Höfle, Bernhard, 2020, "3D Micro-Mapping of Subsidence Stations [Source Code and Data]", https://doi.org/10.11588/data/OU8YA1, heiDATA, V1

This dataset comprises the source code to reproduce the 3D micro-mapping tool for plane adjustment at subsidence stations. In this project, users adjust a plane (height and orientation) at the positions of fixed poles, so-called subsidence stations, to provide information on the...

Sensor-Based Measurements in Paraplegia: Classified References from a Systematic Review

Jan 4, 2020 - Medical Informatics

Benning, Nils-Hendrik; Hagen, Niclas; Knaup, Petra, 2020, "Sensor-Based Measurements in Paraplegia: Classified References from a Systematic Review", https://doi.org/10.11588/data/JRVJGN, heiDATA, V1, UNF:6:f63Fk7qwB3+Tc3vOEqFdnA== [fileUNF]

This dataset contains the results (publication references) of the systematic review "Current Use of Sensor-Based Measurements for Paraplegics", presented at MIE 2020, Geneva.

GER_SET: Situation Entity Type labelled corpus for German

Dec 10, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)

Becker, Maria, 2019, "GER_SET: Situation Entity Type labelled corpus for German", https://doi.org/10.11588/data/BBQYD0, heiDATA, V1

Semantic clause types, also called Situation Entity (SE) types (Smith, 2003) are linguistic characterizations of aspectual properties shown to be useful for tasks like argumentation structure analysis (Becker et al., 2016), genre characterization (Palmer and Friedrich, 2014), and...

Genre-sensitive Neural Situation Entity classifier (DE, EN)

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...

COREC – A neural multi-label COmmonsense RElation Classification system

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...

Affixoid Dataset (DE)

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...

The MSC Data Set

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...

Multilingual Modal Sense Classification using a Convolutional Neural Network [Source Code]

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...

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