Aligning Actions Across Recipe Graphs

Lucia Donatelli, Theresa Schmidt, Debanjali Biswas, Arne Köhn, Fangzhou Zhai, Alexander Koller


Abstract
Recipe texts are an idiosyncratic form of instructional language that pose unique challenges for automatic understanding. One challenge is that a cooking step in one recipe can be explained in another recipe in different words, at a different level of abstraction, or not at all. Previous work has annotated correspondences between recipe instructions at the sentence level, often glossing over important correspondences between cooking steps across recipes. We present a novel and fully-parsed English recipe corpus, ARA (Aligned Recipe Actions), which annotates correspondences between individual actions across similar recipes with the goal of capturing information implicit for accurate recipe understanding. We represent this information in the form of recipe graphs, and we train a neural model for predicting correspondences on ARA. We find that substantial gains in accuracy can be obtained by taking fine-grained structural information about the recipes into account.
Anthology ID:
2021.emnlp-main.554
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Editors:
Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
6930–6942
Language:
URL:
https://aclanthology.org/2021.emnlp-main.554
DOI:
10.18653/v1/2021.emnlp-main.554
Bibkey:
Cite (ACL):
Lucia Donatelli, Theresa Schmidt, Debanjali Biswas, Arne Köhn, Fangzhou Zhai, and Alexander Koller. 2021. Aligning Actions Across Recipe Graphs. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 6930–6942, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Aligning Actions Across Recipe Graphs (Donatelli et al., EMNLP 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/improve-issue-templates/2021.emnlp-main.554.pdf
Video:
 https://preview.aclanthology.org/improve-issue-templates/2021.emnlp-main.554.mp4
Code
 coli-saar/ara
Data
Microsoft Research Multimodal Aligned Recipe Corpus