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20172023
most citedA Survey on Explainability in Machine Reading Comprehension

32 citations · 122 across the 25 of their papers we have counts for

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Showing 2018 · cs.CLShow all

9 papers · 2 filters

cs.CL2018

Graphene: A Context-Preserving Open Information Extraction System

Matthias Cetto, Christina Niklaus, André Freitas +1

We introduce Graphene, an Open IE system whose goal is to generate accurate, meaningful and complete propositions that may facilitate a variety of downstream semantic applications.…

cs.CL2018

Graphene: Semantically-Linked Propositions in Open Information Extraction

Matthias Cetto, Christina Niklaus, André Freitas +1

We present an Open Information Extraction (IE) approach that uses a two-layered transformation stage consisting of a clausal disembedding layer and a phrasal disembedding layer, to…

cs.CL2018

Building a Knowledge Graph from Natural Language Definitions for Interpretable Text Entailment Recognition

Vivian S. Silva, André Freitas, Siegfried Handschuh

Natural language definitions of terms can serve as a rich source of knowledge, but structuring them into a comprehensible semantic model is essential to enable them to be used in s…

cs.CL2018

Semantic Relation Classification: Task Formalisation and Refinement

Vivian S. Silva, Manuela Hürliman, Brian Davis +2

The identification of semantic relations between terms within texts is a fundamental task in Natural Language Processing which can support applications requiring a lightweight sema…

cs.CL2018

Categorization of Semantic Roles for Dictionary Definitions

Vivian S. Silva, Siegfried Handschuh, André Freitas

Understanding the semantic relationships between terms is a fundamental task in natural language processing applications. While structured resources that can express those relation…

cs.CL2018

Word Tagging with Foundational Ontology Classes: Extending the WordNet-DOLCE Mapping to Verbs

Vivian S. Silva, André Freitas, Siegfried Handschuh

Semantic annotation is fundamental to deal with large-scale lexical information, mapping the information to an enumerable set of categories over which rules and algorithms can be a…