31 to 40 of 84 Results
Jan 20, 2021 - Empirical Linguistics and Computational Language Modeling (LiMo)
van den Berg, Esther; Korfhage, Katharina; Ruppenhofer, Josef; Wiegand, Michael; Markert, Katja, 2020, "German Twitter Titling Corpus", https://doi.org/10.11588/data/AOSUY6, heiDATA, V2, UNF:6:14BxjwJS7Q3mfI6ei7iBBw== [fileUNF]
The German Titling Twitter Corpus consists of 1904 stance-annotated tweets collected in June/July 2018 mentioning 24 German politicians with a doctoral degree. The Addendum contains an additional 296 stance-annotated tweets from each month of 2018 mentioning 10 politicians with a... |
Sep 2, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Wiegand, Michael, 2019, "GermEval-2018 Corpus (DE)", https://doi.org/10.11588/data/0B5VML, heiDATA, V1
This dataset comprises the training and test data (German tweets) from the GermEval 2018 Shared on Offensive Language Detection. |
Mar 21, 2023 - Ground truth data for HTR on South Asian Scripts
Derrick, Tom; British Library, 2023, "Ground Truth transcriptions for training OCR of historical Bengali printed texts – Recognition of Early Indian Printed Documents competition - updated with improved XML coordinates", https://doi.org/10.11588/data/AIQSXL, heiDATA, V1
This dataset comprises 81 digitised images (TIFF files) drawn from a selection of early printed Bengali books (1713-1914) digitised through the Two Centuries of Indian Print project (https://www.bl.uk/projects/two-centuries-of-indian-print). Also contained are ground truth transc... |
Nov 13, 2023 - Neural Techniques for German Dependency Parsing
Do, Bich-Ngoc; Rehbein, Ines; Frank, Anette, 2023, "Head Selection Parsers and LSTM Labelers", https://doi.org/10.11588/data/BPWWJL, heiDATA, V1
This resource contains code, data and pre-trained models for various types of neural dependency parsers and LSTM labelers used in the papers: Do et al. (2017). "What Do We Need to Know About an Unknown Word When Parsing German" Do and Rehbein (2017). "Evaluating LSTM Models for G... |
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... |
Feb 26, 2024 - RATIO_EXPLAIN
Becker, Maria, 2024, "IKAT-DE", https://doi.org/10.11588/data/4BA5LY, heiDATA, V1
A corpus consisting of high-quality human annotations of missing and implied information in argumentative texts (German version). The data is further annotated with semantic clause types and commonsense knowledge relations. |
Becker, Maria, 2024, "IKAT-EN", https://doi.org/10.11588/data/RUBM2E, heiDATA, V1, UNF:6:To3aHa8xO8P28fzpCz1Qvw== [fileUNF]
A corpus consisting of high-quality human annotations of missing and implied information in argumentative texts (English version). The data is further annotated with semantic clause types and commonsense knowledge relations. |
Nov 2, 2023 - Heidelberg Centre for Transcultural Studies (HCTS)
Henke, Konstantin; Arnold, Matthias, 2023, "Jing bao ground truth – text block crops and annotations", https://doi.org/10.11588/data/PVYWKB, heiDATA, V1
This is the data set related to the paper "Language Model Assisted OCR Classification for Republican Chinese Newspaper Text", JDADH 11/2023. In this work, we present methods to obtain a neural optical character recognition (OCR) tool for article blocks in a Republican Chinese new... |
Aug 19, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Kotnis, Bhushan, 2019, "KGE Algorithms", https://doi.org/10.11588/data/CSXYSS, heiDATA, V1
An updated method for link prediction that uses a regularization factor that models relation argument types Abstract (Kotnis and Nastase, 2017): Learning relations based on evidence from knowledge repositories relies on processing the available relation instances. Knowledge repos... |
Sep 2, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Wiegand, Michael, 2019, "Lexicon of Abusive Words (EN)", https://doi.org/10.11588/data/MKPEYV, heiDATA, V1
This goldstandard contains a bootstrapped lexicon of abusive words. The lexicon comprises a large set of English negative polar expressions annotated as either abusive or not. |
