Weighted parsing for grammar-based language models
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
We develop a general framework for weighted parsing which is built on top of grammar-based language models and employs flexible weight algebras. It generalizes previous work in that area (semiring parsing, weighted deductive parsing) and also covers applications outside the classical scope of parsing, e.g., algebraic dynamic programming. We show an algorithm which terminates and is correct for a large class of weighted grammar-based language models.
Details
Original language | English |
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Title of host publication | Proceedings of the 14th International Conference on Finite-State Methods and Natural Language Processing (FSMNLP 2019) |
Publisher | The Association for Computational Linguistics |
Pages | 46–55 |
Publication status | Published - 2019 |
Peer-reviewed | Yes |
Keywords
Keywords
- weighted parsing, language model, grammar, language model, grammar