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Generating Typed Dependency Parses from Phrase Structure Parses
Open accessAbstract
This paper describes a system for extracting typed dependency parses of English sentences from phrase structure parses.In order to capture inherent relations occurring in corpus texts that can be critical in real-world applications, many NP relations are included in the set of grammatical relations used.We provide a comparison of our system with Minipar and the Link parser.The typed dependency extraction facility described here is integrated in the Stanford Parser, available for download.
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Cited by
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“thod works at a finer level and embeds fragments of images and fragments of sentences. This method breaks down the images into a number of objects and sentences into a dependency tree relations (DTR) [28] and reasons about their latent, inter-modal alignment. It shows that the method achieves significant improvements…”
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Metadata
- Authors
- de Marneffe, M.-C., MacCartney, B., & Manning, C. D.
- Venue
- Language Resources and Evaluation Conference (LREC)
- Published
- 2006-05-01
- Pages
- 449-454
- OpenAlex
- W1508977358
- Cited by
- 2,258
- References
- 0
- FWCI
- 40.58
- Type
- conference paper
- Language
- en
- Open access
- hybrid
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- CoChat. (2026). Citation check: Generating Typed Dependency Parses from Phrase Structure Parses. https://app.cochat.ai/papers/10.63317/3wtkaidk6ea8
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- de Marneffe, M.-C., MacCartney, B., & Manning, C. D. (2006). Generating Typed Dependency Parses from Phrase Structure Parses. Language Resources and Evaluation Conference (LREC). https://doi.org/10.63317/3wtkaidk6ea8
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
