| Challenge: | Annotated corpus of English cooking recipe procedures with domain-specific linguistic and semantic structure. |
| Approach: | They annotate a corpus of English cooking recipe procedures with domain-specific linguistic and semantic structure and then use a flow graph to represent the sequence of steps. |
| Outcome: | The proposed methods achieve 71.1 to 87.5 F1 in the cooking domain and a flow graph achieves similarity to those used in Japanese recipes. |
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| Challenge: | Existing approaches to translate recipes into a flow graph have performance problems . authors propose a framework to construct a graph from recipe text . |
| Approach: | They propose a framework that can be used to translate recipes into a flow graph representation. |
| Outcome: | The proposed framework can predict the edge label and achieve the overall F1 score of 92.2 on the English recipe flow graph corpus. |
Aligning Actions Across Recipe Graphs (2021.emnlp-main)
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| Challenge: | a recipe explains step by step how to cook a dish, but recipes differ in which cooking actions they describe explicitly, how they describe them, and in which order. |
| Approach: | They propose a recipe corpus which annotates cooking steps in recipes at sentence level . they train a neural model to predict recipes on ARA and model it for automatic understanding . |
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End-to-end Parsing of Procedural Text into Flow Graphs (2024.lrec-main)
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| Challenge: | Existing flow graph parsers lack sufficient annotated data to train them . a lack of annotation can cause costly training, and poor flow graph training results in a large improvement. |
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Building Hierarchically Disentangled Language Models for Text Generation with Named Entities (2020.coling-main)
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| Challenge: | Named entities pose a unique challenge to traditional methods of language modeling. |
| Approach: | They propose a Hierarchically Disentangled Model for named entities in cooking recipes using a dataset from several publicly available online sources. |
| Outcome: | The proposed model is based on 158,473 cooking recipes from public sources. |
Recipe Instruction Semantics Corpus (RISeC): Resolving Semantic Structure and Zero Anaphora in Recipes (2020.aacl-main)
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| Challenge: | Existing approaches to understanding recipe instructions make assumptions that are domain specific. |
| Approach: | They propose a new dataset for information extraction on recipes . they avoid a priori pre-defining domain-specific predicates to recognize . instead, they focus on basic understanding of the expressed semantics . |
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What does it take to bake a cake? The RecipeRef corpus and anaphora resolution in procedural text (2022.findings-acl)
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| Challenge: | Current research on anaphora resolution is mostly based on declarative text, such as chemical patents or instruction manuals. |
| Approach: | They propose a framework for anaphora annotation for the chemical domain for modeling anamorphic phenomena in recipes and chemical patents. |
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Visual Grounding Annotation of Recipe Flow Graph (2020.lrec-1)
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Taichi Nishimura, Suzushi Tomori, Hayato Hashimoto, Atsushi Hashimoto, Yoko Yamakata, Jun Harashima, Yoshitaka Ushiku, Shinsuke Mori
| Challenge: | Existing studies have ground visual observations with procedural texts with graphs to understand which objects are aligned with textual descriptions. |
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ReciFine: Finely Annotated Recipe Dataset for Controllable Recipe Generation (2026.findings-eacl)
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| Challenge: | Existing resources, such as RecipeNLG, extract food items only from ingredient lists, overlooking entities expressed in instructions, such tools, chef actions, food and tool states, and durations. |
| Approach: | They extend RecipeNLG to extract 97 million entities from 2.2 million recipes. |
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Visual Recipe Flow: A Dataset for Learning Visual State Changes of Objects with Recipe Flows (2022.coling-1)
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Keisuke Shirai, Atsushi Hashimoto, Taichi Nishimura, Hirotaka Kameko, Shuhei Kurita, Yoshitaka Ushiku, Shinsuke Mori
| Challenge: | a new dataset enables us to learn a cooking action result for each object in a recipe text. |
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Chop and Change: Anaphora Resolution in Instructional Cooking Videos (2022.findings-aacl)
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| Challenge: | temporally evolving entities present challenges for anaphora resolution tasks . recipes provide rich source for referring expressions of transformed entities . |
| Approach: | They propose to use annotations to annotate recipes for anaphora resolution task . they propose to employ temporal features to improve anamorphic resolution . |
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