SNePS Considered as a Fully Intensional Propositional Semantic Network

Shapiro, Stewart; Rapaport, William J.

doi:10.1007/978-1-4612-4792-0_11

Cited by 93 publications

(64 citation statements)

References 19 publications

(13 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is equivalent to the techniques developed independently by Kintsch & van Dijk 1978 and in Discourse Representation Theory (Kamp & Reyle 1993). See Shapiro 1979Rapaport & Shapiro 1984;Rapaport 1986b;Shapiro & Rapaport 1987 view of semantics espoused by most contemporary linguists (Szabó 2007), as well as most approaches to vocabulary instruction and the use of dictionaries. There are, however, some clear exceptions, such as the lexicographer's method of determining word meanings from actual uses of the word (Murray 1977): "Lexicographers have to define words in situ, not in the abstract, removed from context" (Gilman 1989).…”

Section: Sternberg Et Almentioning

confidence: 99%

“…Metaphysical internalism has proven useful in artificial intelligence (AI) and cognitive modeling (Shapiro & Rapaport 1987.…”

Section: Castañeda's Guise Theorymentioning

confidence: 99%

“…This is equivalent to the techniques developed independently by van Dijk 1978 and in Discourse Representation Theory (Kamp &Reyle 1993). See Shapiro 1979Shapiro , 1982Rapaport & Shapiro 1984;Rapaport 1986b;Shapiro & Rapaport 1987 And Quine (1961) noted that "the primary vehicle of meaning came to be seen no longer in the term but in the statement." 13 This has also been recognized in the field of vocabulary acquisition in the teaching of reading: "while context always determines the meaning of a word, it does not necessarily reveal that meaning" (Deighton 1959).…”

mentioning

confidence: 97%

“…The univocality of language is the claim that talk and thought about truth and reality behaves exactly the same as talk and thought about falsehood and fiction: Language treats objects of both kinds of talk and thought in the same way. This is associated with a principle of "metaphysical internalism": Talk and thought about the world is internal to experience; the (experienced) world must be understood from the "inside", not "externally"-from a first-person point of view, not from God's point of view or Nagel's (1986) "view from nowhere".Metaphysical internalism has proven useful in artificial intelligence (AI) and cognitive modeling (Shapiro & Rapaport 1987.According to guise theory, there are properties, sets of properties (called "guise cores"), and an "individuating operator" (c) that maps guise cores to guises. E.g., where Round is the property of being round and Square is the property of being square, c{Round, Square} is the guise: the round square.…”

mentioning

confidence: 99%

“…The latter can be accomplished by using Meinongian objects. This was later applied to give a semantics for the SNePS semantic network, knowledgerepresentation and reasoning system (Shapiro & Rapaport 1987;see §2.4.4, below). Rapaport 1981 suggested a way to extend the theory: Instead of viewing Meinongian objects as structures of properties, where the meaning of a term such as 'bachelor' (using the double-bracket notation for the meaning-function, this will be denoted as:…”

mentioning

confidence: 99%

See 4 more Smart Citations

Contextual Vocabulary Acquisition: from Algorithm to Curriculum

Rapaport¹,

Kibby²

2014

Castañeda and His Guises

Self Cite

View full text Add to dashboard Cite

Deliberate contextual vocabulary acquisition (CVA) is a reader's ability to figure out a (not the) meaning for an unknown word from its "context", without external sources of help such as dictionaries or people. The appropriate context for such CVA is the "belief-revised integration" of the reader's prior knowledge with the reader's "internalization" of the text. We discuss unwarranted assumptions behind some classic objections to CVA, and present and defend a computational theory of CVA that we have adapted to a new classroom curriculum designed to help students use CVA to improve their reading comprehension. Running head: Contextual Vocabulary Acquisition Keywords:Artificial Intelligence, Education, Linguistics, Philosophy; Instruction, Language acquisition, Language understanding, Learning, Reasoning, Semantics; Knowledge representation, Logic, Symbolic computational modeling.2 From Guise Theory to Contextual Vocabulary Acquisition An Opening AnecdoteWhen Hector-Neri Castañeda was ill, Randall R. Dipert and I (WJR) visited him in Bloomington. He was weak and tired, and his speech was even harder to decipher than it had been when he was healthy. He was happy to see us, however, and, after a few preliminaries, suggested that we have dinner later at his favorite macrobiotic restaurant.The restaurant was exceedingly noisy, rendering dinner conversation virtually impossible. Although he was tired after dinner, he insisted that we come back to his house to talk philosophy. And, as soon as we began our philosophical conversation, his stamina returned, his voice became stronger and clearer, and we were back with the Hector of old. Philosophy gave him strength. Castañeda's Guise Theory.Guise theory (Castañeda 1972(Castañeda , 1999, and many works in between; for a summary, see Rapaport 2005b) has two goals: to serve as a theory of the mechanism of reference and to serve as a theory of the world as it appears to us.And it has two principal sources: Frege's (1892) puzzle of reference and the "univocality" of language. Frege's puzzle concerns the way in which the President of the US is the "same" as the Commander-in-Chief of the US Armed Forces. The univocality of language is the claim that talk and thought about truth and reality behaves exactly the same as talk and thought about falsehood and fiction: Language treats objects of both kinds of talk and thought in the same way. This is associated with a principle of "metaphysical internalism": Talk and thought about the world is internal to experience; the (experienced) world must be understood from the "inside", not "externally"-from a first-person point of view, not from God's point of view or Nagel's (1986) "view from nowhere".Metaphysical internalism has proven useful in artificial intelligence (AI) and cognitive modeling (Shapiro & Rapaport 1987.According to guise theory, there are properties, sets of properties (called "guise cores"), and an "individuating operator" (c) that maps guise cores to guises. E.g., where Round is the property of being round and Squ...

show abstract

Section: Sternberg Et Almentioning

confidence: 99%

“…Metaphysical internalism has proven useful in artificial intelligence (AI) and cognitive modeling (Shapiro & Rapaport 1987.…”

Section: Castañeda's Guise Theorymentioning

confidence: 99%

mentioning

confidence: 97%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Contextual Vocabulary Acquisition: from Algorithm to Curriculum

Rapaport¹,

Kibby²

2014

Castañeda and His Guises

Self Cite

View full text Add to dashboard Cite

show abstract

Tracing the origins of the semantic web

Guns

2013

J Am Soc Inf Sci Tec

View full text Add to dashboard Cite

The Semantic Web has been criticized for not being semantic. This article examines the questions of why and how the Web of Data, expressed in the Resource Description Framework (RDF), has come to be known as the Semantic Web. Contrary to previous papers, we deliberately take a descriptive stance and do not start from preconceived ideas about the nature of semantics. Instead, we mainly base our analysis on early design documents of the (Semantic) Web. The main determining factor is shown to be link typing, coupled with the influence of online metadata. Both factors already were present in early web standards and drafts. Our findings indicate that the Semantic Web is directly linked to older artificial intelligence work, despite occasional claims to the contrary. Because of link typing, the Semantic Web can be considered an example of a semantic network. Originally network representations of the meaning of natural language utterances, semantic networks have eventually come to refer to any networks with typed (usually directed) links. We discuss possible causes for this shift and suggest that it may be due to confounding paradigmatic and syntagmatic semantic relations.

show abstract

The prolog language: Artificial intelligence applications, relevance to the systems community, and a review of seven texts, by James L. Snell, Dept. of Mathematics and Computer Science, SUNY College at Brockport, Brockport, NY 14420, U.S.A.

Snell

1989

Systems Research

View full text Add to dashboard Cite

Prolog is a relatively new computer programming language, developed for Artificial Intelligence, that provides automatic inference from given facts and rules. Prolog is of interest to the Systems community, since it is suited to modeling complex qualitative relationships involving uncertainty, continual change, and self‐modification. This article includes a description of Prolog, some of its present applications, its relevance to Systems research, a brief tutorial, and comparative reviews of seven books on the language.

show abstract

SNePS Considered as a Fully Intensional Propositional Semantic Network

Cited by 93 publications

References 19 publications

Contextual Vocabulary Acquisition: from Algorithm to Curriculum

Contextual Vocabulary Acquisition: from Algorithm to Curriculum

Tracing the origins of the semantic web

The prolog language: Artificial intelligence applications, relevance to the systems community, and a review of seven texts, by James L. Snell, Dept. of Mathematics and Computer Science, SUNY College at Brockport, Brockport, NY 14420, U.S.A.

Contact Info

Product

Resources

About