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English recipe flow graph corpus
conference contribution
posted on 2023-06-09, 21:16 authored by Yoko Yamakata, Shinsuke Mori, John CarrollWe present an annotated corpus of English cooking recipe procedures, and describe and evaluate computational methods for learning these annotations. The corpus consists of 300 recipes written by members of the public, which we have annotated with domain-specific linguistic and semantic structure. Each recipe is annotated with (1) `recipe named entities' (r-NEs) specific to the recipe domain, and (2) a flow graph representing in detail the sequencing of steps, and interactions between cooking tools, food ingredients and the products of intermediate steps. For these two kinds of annotations, inter-annotator agreement ranges from 82.3 to 90.5 F1, indicating that our annotation scheme is appropriate and consistent. We experiment with producing these annotations automatically. For r-NE tagging we train a deep neural network NER tool; to compute flow graphs we train a dependency-style parsing procedure which we apply to the entire sequence of r-NEs in a recipe.In evaluations, our systems achieve 71.1 to 87.5 F1, demonstrating that our annotation scheme is learnable.
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Publication status
- Published
File Version
- Published version
Journal
Proceedings of the 12th Language Resources and Evaluation ConferencePublisher
European Language Resources Association (ELRA)Publisher URL
Page range
5187-5194Pages
8.0Event name
12th Language Resources and Evaluation ConferenceEvent location
Marseille, FranceEvent type
conferenceEvent date
11th - 16th May 2020Department affiliated with
- Informatics Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2020-06-08First Open Access (FOA) Date
2020-06-08First Compliant Deposit (FCD) Date
2020-06-08Usage metrics
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