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Studies in Analytical Reproducibility: the Conquaire Project ...
Cimiano, Philipp; Pietsch, Christian; Wiljes, Cord. - : Universität Bielefeld, 2021
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Bridging the Gap Between Ontology and Lexicon via Class-Specific Association Rules Mined from a Loosely-Parallel Text-Data Corpus ...
Ell, Basil; Elahi, Mohammad Fazleh; Cimiano, Philipp. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021
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3
Linguistic linked data: representation, generation and applications
Cimiano, Philipp; Chiarcos, Christian; McCrae, John P. - : Springer International Publishing AG, 2020
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4
Recent Developments for the Linguistic Linked Open Data Infrastructure ...
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Recent Developments for the Linguistic Linked Open Data Infrastructure ...
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Recent Developments for the Linguistic Linked Open Data Infrastructure ...
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Recent Developments for the Linguistic Linked Open Data Infrastructure ...
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Recent Developments for the Linguistic Linked Open Data Infrastructure ...
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9
D3.2 Research Challenge Report v2 ...
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10
D5.1 Report on Vocabularies for Interoperable Language Resources and Services ...
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11
D5.1 Report on Vocabularies for Interoperable Language Resources and Services ...
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12
D3.2 Research Challenge Report v2 ...
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13
Recent Developments for the Linguistic Linked Open Data Infrastructure ...
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14
Terme-à-LLOD: Simplifying the Conversion and Hosting of Terminological Resources as Linked Data ...
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Terme-à-LLOD: Simplifying the Conversion and Hosting of Terminological Resources as Linked Data ...
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16
How to make a wheelchair understand spoken commands
Couto-Vale, Daniel [Verfasser]; Bateman, John [Akademischer Betreuer]; Bateman, John [Gutachter]. - Bremen : Staats- und Universitätsbibliothek Bremen, 2019
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17
Zero-Shot Cross-Lingual Opinion Target Extraction ...
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18
Extending Neural Question Answering with Linguistic Input Features ...
Abstract: Considerable progress in neural question answering has been made on competitive general domain datasets. In order to explore methods to aid the generalization potential of question answering models, we reimplement a state-of-the-art architecture, perform a parameter search on an open-domain dataset and evaluate a first approach for integrating linguistic input features such as part-of-speech tags, syntactic dependency relations and semantic roles. The results show that adding these input features has a greater impact on performance than any of the architectural parameters we explore. Our findings suggest that these layers of linguistic knowledge have the potential to substantially increase the generalization capacities of neural QA models, thus facilitating cross-domain model transfer or the development of domain-agnostic QA models. ...
URL: https://zenodo.org/record/3373529
https://dx.doi.org/10.5281/zenodo.3373529
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Extending Neural Question Answering with Linguistic Input Features ...
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AMUSE: Multilingual Semantic Parsing for Question Answering over Linked Data ...
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