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Nov 13, 2023 - Neural Techniques for German Dependency Parsing
Do, Bich-Ngoc; Rehbein, Ines, 2023, "Datasets for Dependency Tree Reranking", https://doi.org/10.11588/data/E5NOYH, heiDATA, V1
This resource contains the datasets for dependency tree reranking in 3 languages: English, German and Czech. The creation, analysis and experiment results of the datasets are described in the paper: Do and Rehbein (2020). "Neural Reranking for Dependency Parsing: An Evaluation". |
Nov 13, 2023 - Neural Techniques for German Dependency Parsing
Do, Bich-Ngoc; Rehbein, Ines, 2023, "Real-World PP Attachment Disambiguation Dataset", https://doi.org/10.11588/data/NB46XR, heiDATA, V1
This resource contains a German dataset for real-world PP attachment disambiguation. The creation, analysis and experiment results of the dataset are described in the paper: Do and Rehbein (2020). "Parsers Know Best: German PP Attachment Revisited" |
Oct 25, 2023 - Data Analysis and Modeling in Medicine
Marvin Kinz, 2023, "SimTool-SynBench", https://doi.org/10.11588/data/R9IKCF, heiDATA, V2
The SimTool is a toolset to simulate soft tissue deformation during resection surgery. The proposed toolset is an assimilation of 3D packages in Python and Unreal Engine 4 (UE4) with Nvidia Flex integration, which make it possible to adapt the dataset for more applications. The S... |
Jul 14, 2022 - Computer Assisted Clinical Medicine
Zöllner, Frank, 2022, "Synthesis of CT images from digital body phantoms using CycleGAN [dataset]", https://doi.org/10.11588/data/7NRFYC, heiDATA, V1
The potential of medical image analysis with neural networks is limited by the restricted availability of extensive data sets. The incorporation of synthetic training data is one approach to bypass this shortcoming, as synthetic data offer accurate annotations and unlimited data... |
Mar 7, 2022 - Theoretical Physics
Li, Kunhe; Oiwa, Nestor Norio; Cordeiro, Claudette E.; Heermann, Dieter W., 2022, "Prediction and Comparative Analysis of CTCF Binding Sites based on a First Principle Approach [Research Data]", https://doi.org/10.11588/data/RDISCE, heiDATA, V1
The file contains the CTCF-DNA binding sites for complete genome of Homo sapiens (human), Mus musculus (mouse), Sus scrofa (pig), Capra hircus (goat), Aedes aegypti (dengue and yellow fever mosquito) and Drosophila melanogaster (fruit fly) using electronic nucleotide alignment. T... |
Mara, Hubert, 2019, "HeiCuBeDa Hilprecht - Heidelberg Cuneiform Benchmark Dataset for the Hilprecht Collection", https://doi.org/10.11588/data/IE8CCN, heiDATA, V2
The number of known cuneiform tablets is assumed to be in the hundreds of thousands. A fraction has been published by printing photographs and manual tracings in books, which is collected by the online Cuneiform Digital Library Initiative (CDLI) catalog including some of these im... |
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... |
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... |
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 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... |
