--- license: mit task_categories: - text-classification language: - en tags: - creative problem solving - puzzles - fixation effect - large language models - only connect - quiz show - connecting walls pretty_name: Only Connect Wall Dataset size_categories: - n<1K ---

Alt text Only Connect Wall (OCW) Dataset

The Only Connect Wall (OCW) dataset contains 618 _"Connecting Walls"_ from the [Round 3: Connecting Wall](https://en.wikipedia.org/wiki/Only_Connect#Round_3:_Connecting_Wall) segment of the [Only Connect quiz show](https://en.wikipedia.org/wiki/Only_Connect), collected from 15 seasons' worth of episodes. Each wall contains the ground-truth __groups__ and __connections__ as well as recorded human performance. Please see [our paper](https://arxiv.org/abs/2306.11167) and [GitHub repo](https://github.com/TaatiTeam/OCW) for more details about the dataset and its motivations. ## Usage ```python # pip install datasets from datasets import load_dataset dataset = load_dataset("TaatiTeam/OCW") # The dataset can be used like any other HuggingFace dataset # E.g. get the wall_id of the first example in the train set dataset["train"]["wall_id"][0] # or get the words of the first 10 examples in the test set dataset["test"]["words"][0:10] ``` We also provide two different versions of the dataset where the red herrings in each wall have been significantly reduced (`ocw_randomized`) or removed altogether (`ocw_wordnet`) which can be loaded like: ```python # pip install datasets from datasets import load_dataset ocw_randomized = load_dataset("TaatiTeam/OCW", "ocw_randomized") ocw_wordnet = load_dataset("TaatiTeam/OCW", "ocw_wordnet") ``` See [our paper](https://arxiv.org/abs/2306.11167) for more details. ## 📝 Citing If you use the Only Connect dataset in your work, please consider citing our paper: ``` @article{alavi2024large, title={Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset}, author={Alavi Naeini, Saeid and Saqur, Raeid and Saeidi, Mozhgan and Giorgi, John and Taati, Babak}, journal={Advances in Neural Information Processing Systems}, volume={36}, year={2024} } ``` ## 🙏 Acknowledgements We would like the thank the maintainers and contributors of the fan-made and run website [https://ocdb.cc/](https://ocdb.cc/) for providing the data for this dataset. We would also like to thank the creators of the Only Connect quiz show for producing such an entertaining and thought-provoking show.