CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
ConceptNet — A Practical Commonsense Reasoning Tool-Kit
BT Technology Journal
Natural language directed inference from ontologies
Artificial Intelligence
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
InferenceNet.Br: expression of inferentialist semantic content of the Portuguese language
PROPOR'10 Proceedings of the 9th international conference on Computational Processing of the Portuguese Language
A description logic for inferencenet.br
PROPOR'12 Proceedings of the 10th international conference on Computational Processing of the Portuguese Language
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One of the growing needs related to systems of Natural Language Processing (NLP) is that such systems must be able to perform enriched textual inferences. We argue that one reason for the current limitation of the inferences generated by these systems is that---for the most part---they are based on the characteristics of the things represented by names, and seek to draw inferences based on such characteristics. In this work, we propose the Semantic Inferentialism Model (SIM), which follows a natural path and represents a new paradigm: it seeks to express the inferential capacity of concepts and how these concepts, combined in sentence structures, contribute to the inferential power of sentences. We present a SIM-based Information Extraction System and a pre-evaluation of the results.