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Okuno, Akiko; Cameron-Faulkner, Thea R.; Theakston, Anna L. – Language Learning and Development, 2020
Languages differ in how they encode causal events, placing greater or lesser emphasis on the agent or patient of the action. Little is known about how these preferences emerge and the relative influence of cognitive biases and language-specific input at different stages in development. In these studies, we investigated the emergence of sentence…
Descriptors: Language Processing, Contrastive Linguistics, Preferences, Linguistic Input
Honea, Katherine – ProQuest LLC, 2012
Research that examines diachronic change and modality posit that modal verbs follow certain universal paths of development (e.g. Cornillie, 2007; Bybee & Fleischman, 1995; Bybee, Perkins & Pagliuca, 1994). The present study examines the development of Spanish modality in Mexico through the use of multivariate analyses, relative…
Descriptors: Foreign Countries, Spanish, Sociolinguistics, Diachronic Linguistics
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Harrison, Sandra; Morgan, Roger – Language Learning Journal, 2012
There is an increasing sensitivity to the challenges posed by the language of examination papers and of instruction in scientific subjects, especially for non-native speakers of English. It has been observed that in addition to technical subject-specific vocabulary, non-technical words such as instructional verbs have been sources of difficulty,…
Descriptors: Sentences, Manufacturing Industry, Sentence Structure, Computer Software
Kaplan, Ronald M. – 1971
This paper describes the notation and underlying organization of an augmented, recursive-transition network grammar and illustrates how such a grammar is a natural medium for expressing and explaining a wide variety of facts about the psychological processes of sentence comprehension. A general discussion of transformational grammar and…
Descriptors: Algorithms, Cognitive Processes, Computational Linguistics, Computer Programs
Winograd, Terry – 1971
This paper describes a system for the computer understanding of English. The system answers questions, executes commands, and accepts information in normal English dialogue. It uses semantic information and context to understand discourse and to disambiguate sentences. It combines a complete syntactic analysis of each sentence with a heuristic…
Descriptors: Computational Linguistics, Computer Programs, Computers, Deep Structure