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README.md

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-license: cc-by-4.0
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+# Implicit-VidSRL Dataset
+
+- **Paper:** https://arxiv.org/abs/2505.21068
+- **Curated by:** Anil Batra and Laura Sevilla-Lara, Marcus Rohrbach, Frank Keller
+- **Language(s) (NLP):** English
+- **License:** CC-BY-4.0
+
+## Dataset Summary
+
+Implicit-VidSRL is a benchmark for the understanding of procedural steps in instructional videos. 
+The dataset uses semantic role labeling (SRL) to model the semantics of narrated instructional video as simple 
+predicate-argument structures like {verb,what,where/with}. The dataset contains implicit and explicit arguments which can be infered from
+contextual information in multimodal cooking procedures.
+
+## Dataset Details
+
+  ### Dataset Sources
+  - **Youcook2**: http://youcook2.eecs.umich.edu/
+  - **Tasty**: https://cvml.comp.nus.edu.sg/tasty/
+
+  ### Dataset Fields
+
+  Each record in the dataset contains the following fields:
+  - **video_id** (`str`): Video Id from the source dataset.
+  - **dataset** (`str`): The name of the source dataset.
+  - **title** (`int`): The title of the recipe.
+  - **duration** (`str`): Duration of video in seconds.
+  - **timestamps** (`List[List[float]]`): The list of timestamps corresponding to each recipe step in the video. Each timestamp entry contains start and end timestamp.
+  - **sentences** (`List[str]`): The list of steps in the recipe. Each recipe step is natural text in English. 
+  - **srl** (`List[Dict]`): The new annotation for each recipe step. Each list item corresponds to the recipe step with key enteries of verb/what/where containing ingredient entities. In addition it also has information about the implicit entities for each step.
+
+## Citation
+
+```BibTeX
+
+@inproceedings{
+    batra2025implicit,
+    title={Predicting Implicit Arguments in Procedural Video Instructions},
+    author={Anil Batra and Laura Sevilla-Lara, Marcus Rohrbach, Frank Keller},
+    booktitle={The 63rd Annual Meeting of the Association for Computational Linguistics},
+    year={2025}
+}
+```