Abstract Pre-trained language representation models (PLMs) cannot well capture factual knowledge from text. In contrast, embedding (KE) methods can effectively represent the relational facts in graphs (KGs) with informative entity embeddings, but conventional KE take full advantage of abundant textual information. this paper, we propose a unified model for Knowledge Embedding and LanguagERepres...

We argue that a connective element between the three domains, signs, logic and language, could be knowledge representation. This paper is an attempt to show that knowledge can be based on signs, that how knowledge emerges, that has a logical meaning, and that language is a representation of knowledge.

We do not know how humans reason, whether they reason using natural language (NL) or not and we are not interested in proving or disproving such a proposition. Nonetheless, it seems that a very expressive transparent medium humans communicate with, state their problems in and justify how they solve these problems is NL. Hence, we wished to use NL as a Knowledge Representation(KR) in NL knowledg...

We present a system, called IMMIGRANT, which learns rules about the grammar of a second language from instructions. We explore the implications of this task on the representation of linguistic knowledge in a natural language understanding system. We conclude that the internal representation of linguistic knowledge used in IMMIGRANT, which is unification-based, is more amenable to language learn...

Knowledge Representation & Reasoning (KR&R) is a fundamental topic in Artificial Intelligence. A basic KR language is First– Order Logic (FOL), the most representative logic–based representation language, which is part of almost any introductory AI course. In this work we present KRRT (Knowledge Representation & Reasoning Tutor). KRRT is a Web–based system which main goal is to help the student...

This paper proposes building knowledge-based systems using a programming system based on a very-high-level language. It gives an overview of such a programming system, BC, and shows how BC can be used to implement knowledge representation features, providing as examples, automatic maintenance of inverse links and property inheritance. The specification language of BC can be extended to include ...

One problem in the design of a lexicon for natural language processing is the representation of semantic knowledge. We examine the adequacy of knowledge representation formalisms developed in artificial intelligence, in particular of term subsumption languages for these issues. In order to derive some basic requirements for a suitable representation language we analyze a number of definitions o...

This article presents representation of knowledge patterns in RDF language. The approach to knowledge representation can be used in Semantic Web as a tool of finding some additional RDF assertions in the frame of linked data. The article introduces the term “knowledge pattern” and dividing the knowledge patterns into two groups – to Top-level knowledge patterns and to Domain knowledge patterns....