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Quantifiers in natural language: efficient communication and degrees of semantic universals
While the languages of the world vary greatly, they exhibit systematic patterns, as well. Semantic universals are restrictions on the variation in meaning exhibit cross-linguistically (e.g., that, in all languages, expressions of a certain type can only denote meanings with a certain special property). This paper pursues an efficient communication analysis to explain the presence of semantic universals in a domain of function words: quantifiers. Two experiments measure how well languages do in optimally trading off between competing pressures of simplicity and informativeness. First, we show that artificial languages which more closely resemble natural languages are more optimal. Then, we introduce information-theoretic measures of degrees of semantic universals and show that these are not correlated with optimality in a random sample of artificial languages. These results suggest both that efficient communication shapes semantic typology in both content and function word domains, as well as that semantic universals may not stand in need of independent explanation.
Microsoft Academic Graph classification: Artificial intelligence business.industry business Function (engineering) media_common.quotation_subject media_common Natural language processing computer.software_genre computer Variation (linguistics) Problem of universals Natural language Constructed language Meaning (philosophy of language) Computer science Simplicity Function word
semantic universals, efficient communication, quantifiers, monotonicity, conservativity, simplicity, Science, Q, Astrophysics, QB460-466, Physics, QC1-999, General Physics and Astronomy, informativeness, semantic typology, Article
semantic universals, efficient communication, quantifiers, monotonicity, conservativity, simplicity, Science, Q, Astrophysics, QB460-466, Physics, QC1-999, General Physics and Astronomy, informativeness, semantic typology, Article
Microsoft Academic Graph classification: Artificial intelligence business.industry business Function (engineering) media_common.quotation_subject media_common Natural language processing computer.software_genre computer Variation (linguistics) Problem of universals Natural language Constructed language Meaning (philosophy of language) Computer science Simplicity Function word
- University of Mary United States
- UNIVERSITY OF WASHINGTON United States
- University of Washington United States
- University of Amsterdam Netherlands
- Washington State University United States
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- University of Mary United States
- UNIVERSITY OF WASHINGTON United States
- University of Washington United States
- University of Amsterdam Netherlands
- Washington State University United States
While the languages of the world vary greatly, they exhibit systematic patterns, as well. Semantic universals are restrictions on the variation in meaning exhibit cross-linguistically (e.g., that, in all languages, expressions of a certain type can only denote meanings with a certain special property). This paper pursues an efficient communication analysis to explain the presence of semantic universals in a domain of function words: quantifiers. Two experiments measure how well languages do in optimally trading off between competing pressures of simplicity and informativeness. First, we show that artificial languages which more closely resemble natural languages are more optimal. Then, we introduce information-theoretic measures of degrees of semantic universals and show that these are not correlated with optimality in a random sample of artificial languages. These results suggest both that efficient communication shapes semantic typology in both content and function word domains, as well as that semantic universals may not stand in need of independent explanation.