Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 1 |
| Since 2006 (last 20 years) | 2 |
Descriptor
| Computational Linguistics | 2 |
| Figurative Language | 2 |
| Natural Language Processing | 2 |
| Abstract Reasoning | 1 |
| Artificial Intelligence | 1 |
| Computer Software | 1 |
| Cultural Background | 1 |
| Databases | 1 |
| Dictionaries | 1 |
| Information Retrieval | 1 |
| Language Acquisition | 1 |
| More ▼ | |
Author
| Boguslavsky, Igor | 1 |
| Cardenosa, Jesus | 1 |
| Frank, Michael C. | 1 |
| Gallardo, Carolina | 1 |
| Kachergis, George | 1 |
| Mahowald, Kyle | 1 |
Publication Type
| Journal Articles | 2 |
| Reports - Descriptive | 1 |
| Reports - Evaluative | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkMahowald, Kyle; Kachergis, George; Frank, Michael C. – First Language, 2020
Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…
Descriptors: Models, Language Processing, Computational Linguistics, Language Acquisition
Boguslavsky, Igor; Cardenosa, Jesus; Gallardo, Carolina – Applied Linguistics, 2009
Multilingual lexicons are needed in various applications, such as cross-lingual information retrieval, machine translation, and some others. Often, these applications suffer from the ambiguity of dictionary items, especially when an intermediate natural language is involved in the process of the dictionary construction, since this language adds…
Descriptors: Translation, Figurative Language, Multilingualism, Dictionaries
