Elnaz Shafaei-Bajestan, Masoumeh Moradipour-Tari, Peter Uhrig, R. Harald Baayen
{"title":"复数化调色板:通过分布语义揭示英语名词复数化中的语义集群","authors":"Elnaz Shafaei-Bajestan, Masoumeh Moradipour-Tari, Peter Uhrig, R. Harald Baayen","doi":"10.1007/s11525-024-09428-9","DOIUrl":null,"url":null,"abstract":"<p>Using distributional semantics, we show that English nominal pluralization exhibits semantic clusters. For instance, the change in semantic space from singulars to plurals differs depending on whether a word denotes, e.g., a fruit, or an animal. Languages with extensive noun classes such as Swahili and Kiowa distinguish between these kind of words in their morphology. In English, even though not marked morphologically, plural semantics actually also varies by semantic class. A semantically informed method, CosClassAvg, is introduced that is compared to two other methods, one implementing a fixed shift from singular to plural, and one creating plural vectors from singular vectors using a linear mapping (FRACSS). Compared to FRACSS, CosClassAvg predicted plural vectors that were more similar to the corpus-extracted plural vectors in terms of vector length, but somewhat less similar in terms of orientation. Both FRACSS and CosClassAvg outperform the method using a fixed shift vector to create plural vectors, which does not do justice to the intricacies of English plural semantics. A computational modeling study revealed that the observed difference between the plural semantics generated by these three methods carries over to how well a computational model of the listener can understand previously unencountered plural forms. Among all methods, CosClassAvg provides a good balance for the trade-off between productivity (being able to understand novel plural forms) and faithfulness to corpus-extracted plural vectors (i.e., understanding the particulars of the meaning of a given plural form).</p>","PeriodicalId":51849,"journal":{"name":"Morphology","volume":"16 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The pluralization palette: unveiling semantic clusters in English nominal pluralization through distributional semantics\",\"authors\":\"Elnaz Shafaei-Bajestan, Masoumeh Moradipour-Tari, Peter Uhrig, R. Harald Baayen\",\"doi\":\"10.1007/s11525-024-09428-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Using distributional semantics, we show that English nominal pluralization exhibits semantic clusters. For instance, the change in semantic space from singulars to plurals differs depending on whether a word denotes, e.g., a fruit, or an animal. Languages with extensive noun classes such as Swahili and Kiowa distinguish between these kind of words in their morphology. In English, even though not marked morphologically, plural semantics actually also varies by semantic class. A semantically informed method, CosClassAvg, is introduced that is compared to two other methods, one implementing a fixed shift from singular to plural, and one creating plural vectors from singular vectors using a linear mapping (FRACSS). Compared to FRACSS, CosClassAvg predicted plural vectors that were more similar to the corpus-extracted plural vectors in terms of vector length, but somewhat less similar in terms of orientation. Both FRACSS and CosClassAvg outperform the method using a fixed shift vector to create plural vectors, which does not do justice to the intricacies of English plural semantics. A computational modeling study revealed that the observed difference between the plural semantics generated by these three methods carries over to how well a computational model of the listener can understand previously unencountered plural forms. Among all methods, CosClassAvg provides a good balance for the trade-off between productivity (being able to understand novel plural forms) and faithfulness to corpus-extracted plural vectors (i.e., understanding the particulars of the meaning of a given plural form).</p>\",\"PeriodicalId\":51849,\"journal\":{\"name\":\"Morphology\",\"volume\":\"16 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Morphology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s11525-024-09428-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"LANGUAGE & LINGUISTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Morphology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s11525-024-09428-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
The pluralization palette: unveiling semantic clusters in English nominal pluralization through distributional semantics
Using distributional semantics, we show that English nominal pluralization exhibits semantic clusters. For instance, the change in semantic space from singulars to plurals differs depending on whether a word denotes, e.g., a fruit, or an animal. Languages with extensive noun classes such as Swahili and Kiowa distinguish between these kind of words in their morphology. In English, even though not marked morphologically, plural semantics actually also varies by semantic class. A semantically informed method, CosClassAvg, is introduced that is compared to two other methods, one implementing a fixed shift from singular to plural, and one creating plural vectors from singular vectors using a linear mapping (FRACSS). Compared to FRACSS, CosClassAvg predicted plural vectors that were more similar to the corpus-extracted plural vectors in terms of vector length, but somewhat less similar in terms of orientation. Both FRACSS and CosClassAvg outperform the method using a fixed shift vector to create plural vectors, which does not do justice to the intricacies of English plural semantics. A computational modeling study revealed that the observed difference between the plural semantics generated by these three methods carries over to how well a computational model of the listener can understand previously unencountered plural forms. Among all methods, CosClassAvg provides a good balance for the trade-off between productivity (being able to understand novel plural forms) and faithfulness to corpus-extracted plural vectors (i.e., understanding the particulars of the meaning of a given plural form).
期刊介绍:
Aim The aim of Morphology is to publish high quality articles that contribute to the further articulation of morphological theory and linguistic theory in general, or present new and unexplored data. Relevant empirical evidence for the theoretical claims in the articles will be provided by in-depth analyses of specific languages or by comparative, cross-linguistic analyses of the relevant facts. The sources of data can be grammatical descriptions, corpora of data concerning language use and other naturalistic data, and experiments. Scope Morphology publishes articles on morphology proper, as well as articles on the interaction of morphology with phonology, syntax, and semantics, the acquisition and processing of morphological information, the nature of the mental lexicon, and morphological variation and change. Its main focus is on formal models of morphological knowledge, morphological typology (the range and limits of variation in natural languages), the position of morphology in the architecture of the human language faculty, and the evolution and change of language. In addition, the journal deals with the acquisition of morphological knowledge and its role in language processing. Articles on computational morphology and neurolinguistic approaches to morphology are also welcome. The first volume of Morphology appeared as Volume 16 (2006). Previous volumes were published under the title Yearbook of Morphology.