There was an error with your search parameters. Please clear your search and try again.
1 to 8 of 8 Results
Aug 13, 2014 - Database Systems Research Group
Strötgen, Jannik; Gertz, Michael, 2014, "WikiWarsDE Corpus", https://doi.org/10.11588/data/10026, heiDATA, V1
The WikiWarsDE corpus is a German corpus containing Wikipedia articles with annotations of temporal expressions. Its creation was motivated by the English WikiWars corpus (Mazur & Dale 2010). WikiWarsDE was developed to support research on temporal information extraction and norm... |
Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)
Rehbein, Ines; Ruppenhofer, Josef; Do, Bich-Ngoc, 2020, "tweeDe", https://doi.org/10.11588/data/S90S35, heiDATA, V1
A German UD Twitter treebank, with >12,000 tokens from 519 tweets, annotated in the Universal Dependencies framework |
Drees, Bastian, 2016, "Text und Data Mining an wissenschaftlichen Repositorien und Publikationsservern in Deutschland - Zusammenfassung der Ergebnisse einer Umfrage im Februar und März 2016", https://doi.org/10.11588/data/10090, heiDATA, V2
Es wurden die auf den Homepages angegebenen Ansprechpartner wissenschaftlicher Repositorien und Publikationsserver in Deutschland zu ihren Erfahrungen mit Text und Data Mining befragt. Die Befragung fand zwischen dem 22. und 26.2.2016 per E-Mail statt. Es wurden Ansprechpartner v... |
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. |
Jun 16, 2014 - Statistical Natural Language Processing Group
Wäschle, Katharina; Riezler, Stefan, 2014, "PatTR: Patent Translation Resource", https://doi.org/10.11588/data/10002, heiDATA, V3
PatTR is a sentence-parallel corpus extracted from the MAREC patent collection. The current version contains more than 22 million German-English and 18 million French-English parallel sentences collected from all patent text sections as well as 5 million German-French sentence pa... |
Apr 24, 2024 - AIPHES
Mihaylov, Todor, 2024, "Knowledge-Enhanced Neural Networks for Machine Reading Comprehension [Source Code and Additional Material]", https://doi.org/10.11588/data/HU3ARF, heiDATA, V1
Machine Reading Comprehension is a language understanding task where a system is expected to read a given passage of text and typically answer questions about it. When humans assess the task of reading comprehension, in addition to the presented text, they usually use the knowled... |
Jul 15, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Nastase, Vivi; Kotnis, Bhushan, 2019, "Abstract graphs, abstract paths, grounded paths for Freebase and NELL", https://doi.org/10.11588/data/AVLFPZ, heiDATA, V1
We describe a method for representing knowledge graphs that capture an intensional representation of the original extensional information. This representation is very compact, and it abstracts away from individual links, allowing us to find better path candidates, as shown by the... |
Feb 4, 2019 - AIPHES
Marasovic, Ana, 2019, "Abstract Anaphora Resolution [Source Code]", https://doi.org/10.11588/data/UDMPY5, heiDATA, V1
Abstract Anaphora Resolution (AAR) aims to find the interpretation of nominal expressions (e.g., this result, those two actions) and pronominal expressions (e.g., this, that, it) that refer to abstract-object-antecedents such as facts, events, plans, actions, or situations. The f... |
