5 research outputs found
Situated Language Understanding for an Anthropomorphic Robot based on Linguistic Constructions and Embodied Simulation
Priesters M, Schilling M, Kopp S. Situated Language Understanding for an Anthropomorphic Robot based on Linguistic Constructions and Embodied Simulation. Presented at the International Cognitive Linguistics Conference (ICLC-13), Newcastle, UK
Understanding Substructures in Commonsense Relations in ConceptNet
Acquiring commonsense knowledge and reasoning is an important goal in modern
NLP research. Despite much progress, there is still a lack of understanding
(especially at scale) of the nature of commonsense knowledge itself. A
potential source of structured commonsense knowledge that could be used to
derive insights is ConceptNet. In particular, ConceptNet contains several
coarse-grained relations, including HasContext, FormOf and SymbolOf, which can
prove invaluable in understanding broad, but critically important, commonsense
notions such as 'context'. In this article, we present a methodology based on
unsupervised knowledge graph representation learning and clustering to reveal
and study substructures in three heavily used commonsense relations in
ConceptNet. Our results show that, despite having an 'official' definition in
ConceptNet, many of these commonsense relations exhibit considerable
sub-structure. In the future, therefore, such relations could be sub-divided
into other relations with more refined definitions. We also supplement our core
study with visualizations and qualitative analyses.Comment: arXiv admin note: substantial text overlap with arXiv:2011.1408