Search Results for author: S{\"o}ren Auer

Found 4 papers, 1 papers with code

SemEval-2021 Task 11: NLPContributionGraph - Structuring Scholarly NLP Contributions for a Research Knowledge Graph

no code implementations • SEMEVAL 2021 • Jennifer D{'}Souza, S{\"o}ren Auer, Ted Pedersen

The phrase-level annotations were scientific term and predicate phrases from the contribution sentences.

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Fine-tuning BERT with Focus Words for Explanation Regeneration

no code implementations • Joint Conference on Lexical and Computational Semantics 2020 • Isaiah Onando Mulang{'}, Jennifer D{'}Souza, S{\"o}ren Auer

Explanation generation introduced as the world tree corpus (Jansen et al., 2018) is an emerging NLP task involving multi-hop inference for explaining the correct answer in multiple-choice QA.

Explanation Generation Multiple-choice +1

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Team SVMrank: Leveraging Feature-rich Support Vector Machines for Ranking Explanations to Elementary Science Questions

no code implementations • WS 2019 • Jennifer D{'}Souza, Isaiah On Mulang{'}, o, S{\"o}ren Auer

The TextGraphs 2019 Shared Task on Multi-Hop Inference for Explanation Regeneration (MIER-19) tackles explanation generation for answers to elementary science questions.

Explanation Generation Learning-To-Rank +1

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Old is Gold: Linguistic Driven Approach for Entity and Relation Linking of Short Text

1 code implementation • NAACL 2019 • Ahmad Sakor, on, Isaiah o Mulang{'}, Kuldeep Singh, Saeedeh Shekarpour, Maria Esther Vidal, Jens Lehmann, S{\"o}ren Auer

Short texts challenge NLP tasks such as named entity recognition, disambiguation, linking and relation inference because they do not provide sufficient context or are partially malformed (e. g. wrt.

Entity Linking Implicit Relations +5

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