Andrea Gregor de Varda, Daniele Gatti, Marco Marelli, Fritz Günther
{"title":"词性之外的意义:用语言模型捕捉伪词定义","authors":"Andrea Gregor de Varda, Daniele Gatti, Marco Marelli, Fritz Günther","doi":"10.1162/coli_a_00527","DOIUrl":null,"url":null,"abstract":"Pseudowords such as “knackets” or “spechy” – letter strings that are consistent with the orthotactical rules of a language but do not appear in its lexicon – are traditionally considered to be meaningless, and employed as such in empirical studies. However, recent studies that show specific semantic patterns associated with these words as well as semantic effects on human pseudoword processing have cast doubt on this view. While these studies suggest that pseudowords have meanings, they provide only extremely limited insight as to whether humans are able to ascribe explicit and declarative semantic content to unfamiliar word forms. In the present study, we employed an exploratory-confirmatory study design to examine this question. In a first exploratory study, we started from a pre-existing dataset of words and pseudowords alongside human-generated definitions for these items. Employing 18 different language models, we showed that the definitions actually produced for (pseudo)words were closer to their respective (pseudo)words than the definitions for the other items. Based on these initial results, we conducted a second, pre-registered, high-powered confirmatory study collecting a new, controlled set of (pseudo)word interpretations. This second study confirmed the results of the first one. Taken together, these findings support the idea that meaning construction is supported by a flexible form-to-meaning mapping system based on statistical regularities in the language environment that can accommodate novel lexical entries as soon as they are encountered.","PeriodicalId":49089,"journal":{"name":"Computational Linguistics","volume":"55 1","pages":""},"PeriodicalIF":9.3000,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Meaning beyond lexicality: Capturing Pseudoword Definitions with Language Models\",\"authors\":\"Andrea Gregor de Varda, Daniele Gatti, Marco Marelli, Fritz Günther\",\"doi\":\"10.1162/coli_a_00527\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pseudowords such as “knackets” or “spechy” – letter strings that are consistent with the orthotactical rules of a language but do not appear in its lexicon – are traditionally considered to be meaningless, and employed as such in empirical studies. However, recent studies that show specific semantic patterns associated with these words as well as semantic effects on human pseudoword processing have cast doubt on this view. While these studies suggest that pseudowords have meanings, they provide only extremely limited insight as to whether humans are able to ascribe explicit and declarative semantic content to unfamiliar word forms. In the present study, we employed an exploratory-confirmatory study design to examine this question. In a first exploratory study, we started from a pre-existing dataset of words and pseudowords alongside human-generated definitions for these items. Employing 18 different language models, we showed that the definitions actually produced for (pseudo)words were closer to their respective (pseudo)words than the definitions for the other items. Based on these initial results, we conducted a second, pre-registered, high-powered confirmatory study collecting a new, controlled set of (pseudo)word interpretations. This second study confirmed the results of the first one. Taken together, these findings support the idea that meaning construction is supported by a flexible form-to-meaning mapping system based on statistical regularities in the language environment that can accommodate novel lexical entries as soon as they are encountered.\",\"PeriodicalId\":49089,\"journal\":{\"name\":\"Computational Linguistics\",\"volume\":\"55 1\",\"pages\":\"\"},\"PeriodicalIF\":9.3000,\"publicationDate\":\"2024-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Linguistics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1162/coli_a_00527\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Linguistics","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1162/coli_a_00527","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Meaning beyond lexicality: Capturing Pseudoword Definitions with Language Models
Pseudowords such as “knackets” or “spechy” – letter strings that are consistent with the orthotactical rules of a language but do not appear in its lexicon – are traditionally considered to be meaningless, and employed as such in empirical studies. However, recent studies that show specific semantic patterns associated with these words as well as semantic effects on human pseudoword processing have cast doubt on this view. While these studies suggest that pseudowords have meanings, they provide only extremely limited insight as to whether humans are able to ascribe explicit and declarative semantic content to unfamiliar word forms. In the present study, we employed an exploratory-confirmatory study design to examine this question. In a first exploratory study, we started from a pre-existing dataset of words and pseudowords alongside human-generated definitions for these items. Employing 18 different language models, we showed that the definitions actually produced for (pseudo)words were closer to their respective (pseudo)words than the definitions for the other items. Based on these initial results, we conducted a second, pre-registered, high-powered confirmatory study collecting a new, controlled set of (pseudo)word interpretations. This second study confirmed the results of the first one. Taken together, these findings support the idea that meaning construction is supported by a flexible form-to-meaning mapping system based on statistical regularities in the language environment that can accommodate novel lexical entries as soon as they are encountered.
期刊介绍:
Computational Linguistics is the longest-running publication devoted exclusively to the computational and mathematical properties of language and the design and analysis of natural language processing systems. This highly regarded quarterly offers university and industry linguists, computational linguists, artificial intelligence and machine learning investigators, cognitive scientists, speech specialists, and philosophers the latest information about the computational aspects of all the facets of research on language.