A Reflective Architecture for Robust Language Processing and Learning

Becoming a proficient speaker of a language requires more than just learning a set of words and grammar rules, it also implies mastering the ways in which speakers of that language typically innovate: stretching the meaning of words, introducing new grammatical constructions, introducing a new category, and so on. This paper demonstrates that such meta-knowledge can be represented and applied by reusing similar representations and processing techniques as needed for routine linguistic processing, which makes it possible that language processing makes use of computational reflection.

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