Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Artificial Languages | 1 |
| Computational Linguistics | 1 |
| Connected Discourse | 1 |
| Correlation | 1 |
| Inferences | 1 |
| Language Acquisition | 1 |
| Language Research | 1 |
| Learning Processes | 1 |
| Linguistic Input | 1 |
| Models | 1 |
| Semantics | 1 |
| More ▼ | |
Source
| Cognitive Science | 1 |
Publication Type
| Journal Articles | 1 |
| Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Ouyang, Long; Boroditsky, Lera; Frank, Michael C. – Cognitive Science, 2017
Computational models have shown that purely statistical knowledge about words' linguistic contexts is sufficient to learn many properties of words, including syntactic and semantic category. For example, models can infer that "postman" and "mailman" are semantically similar because they have quantitatively similar patterns of…
Descriptors: Semiotics, Computational Linguistics, Syntax, Semantics

Peer reviewed
Direct link
