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1
Can we predict new facts with open knowledge graph embeddings? A benchmark for open link prediction
Gashteovski, Kiril; Gemulla, Rainer; Wang, Yanjie. - : Association for Computational Linguistics, 2020
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2
LibKGE – A knowledge graph embedding library for reproducible research
Broscheit, Samuel; Ruffinelli, Daniel; Kochsiek, Adrian. - : Association for Computational Linguistics (ACL), 2020
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3
On aligning OpenIE extractions with Knowledge Bases: A case study
Gashteovski, Kiril; Gemulla, Rainer; Kotnis, Bhushan. - : Association for Computational Linguistics (ACL), 2020
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4
OPIEC: An open information extraction corpus
Gashteovski, Kiril [Verfasser]; Wanner, Sebastian [Verfasser]; Hertling, Sven [Verfasser]. - Mannheim : Universitätsbibliothek Mannheim, 2019
DNB Subject Category Language
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5
OPIEC: An open information extraction corpus
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6
On evaluating embedding models for knowledge base completion
Gemulla, Rainer; Wang, Yanjie; Broscheit, Samuel; Ruffiinelli, Daniel; Meilicke, Christian. - : Association for Computational Linguistics, 2019
Abstract: Knowledge graph embedding models have recently received significant attention in the literature. These models learn latent semantic representations for the entities and relations in a given knowledge base; the representations can be used to infer missing knowledge. In this paper, we study the question of how well recent embedding models perform for the task of knowledge base completion, i.e., the task of inferring new facts from an incomplete knowledge base. We argue that the entity ranking protocol, which is currently used to evaluate knowledge graph embedding models, is not suitable to answer this question since only a subset of the model predictions are evaluated. We propose an alternative entity-pair ranking protocol that considers all model predictions as a whole and is thus more suitable to the task. We conducted an experimental study on standard datasets and found that the performance of popular embeddings models was unsatisfactory under the new protocol, even on datasets that are generally considered to be too easy. Moreover, we found that a simple rule-based model often provided superior performance. Our findings suggest that there is a need for more research into embedding models as well as their training strategies for the task of knowledge base completion.
Keyword: 004 Informatik
URL: https://madoc.bib.uni-mannheim.de/52546/1/On%20Evaluating%20Embedding%20Models%20for%20Knowledge%20Base%20Completion.pdf
https://madoc.bib.uni-mannheim.de/52546/
https://madoc.bib.uni-mannheim.de/52546
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7
A neural autoencoder approach for document ranking and query refinement in pharmacogenomic information retrieval
Broscheit, Samuel; Pfeiffer, Jonas; Gemulla, Rainer. - : Association for Computational Linguistics, 2018
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8
Learning distributional token representations from visual features
Gemulla, Rainer; Broscheit, Samuel; Keuper, Margret. - : Association for Computational Linguistics, 2018
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9
MinIE: minimizing facts in open information extraction
Corro, Luciano del; Gashteovski, Kiril; Gemulla, Rainer. - : Association for Computational Linguistics, 2017
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10
Methods for open information extraction and sense disambiguation on natural language text ; Methoden der Offenen Informationsextraktion und Bedeutungsdisambiguierung in Texten
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11
FINET: context-aware fine-grained named entity typing
Abujabal, Abdalghani; Corro, Luciano del; Gemulla, Rainer. - : Assoc. for Computational Linguistics, 2015
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12
CORE: Context-aware open relation extraction with factorization machines
Corro, Luciano del; Petroni, Fabio; Gemulla, Rainer. - : Assoc. for Computational Linguistics, 2015
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13
Werdy: Recognition and disambiguation of verbs and verb phrases with syntactic and semantic pruning
Corro, Luciano del [Verfasser]; Gemulla, Rainer [Verfasser]; Weikum, Gerhard [Verfasser]. - Mannheim : Universitätsbibliothek Mannheim, 2014
DNB Subject Category Language
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14
Senti-LSSVM: Sentiment-oriented multi-relation extraction with latent structural SVM
Weikum, Gerhard; Gemulla, Rainer; Zhang, Yi. - : Assoc. for Computational Linguistics, 2014
BASE
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15
Werdy: Recognition and disambiguation of verbs and verb phrases with syntactic and semantic pruning
Corro, Luciano del; Gemulla, Rainer; Weikum, Gerhard. - : Assoc. for Computational Linguistics, 2014
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