ATOMIC is a crowdsourced commonsense knowledge graph that is used for state-of-the-art commonsense reasoning tasks. In this homework, you will be working with COMET-ATOMIC-2020, a BART (encoder-decoder) model finetuned on an updated version of the original ATOMIC. You will take the information provided to you by COMET-ATOMIC-2020 and structure it into a schema used to track the state of a story. (A schema is a structured representation.)
Go to the Python notebook for more information.
You will be filling in 4 methods in the code:
(3 pts) Explain how you made your schema. (i.e., Why did you decide to do the things you did?) (1 paragraph) You can test how your schema does on the “testing call”. Once your schema is finalized, uncomment out the 5 story blocks, and then answer the following questions for each story:
2-6. (1 pt each) What went well when processing this story? What went poorly? (2-3 sentences)
Answer each of the following with a couple of sentences:
2a. (4 pts) Do you think any of the other knowledge bases mentioned in class could better model these? Which ones and why? If none of them could, why not?
hw5.ipynb
that runs your COMET-ATOMIC schema. Important: Save the output for the Story Tracking Questions!Submissions should be done on Blackboard.
Jena D. Hwang, Chandra Bhagavatula, Ronan Le Bras, Jeff Da, Keisuke Sakaguchi, Antoine Bosselut, and Yejin Choi, (COMET-)ATOMIC-2020: On Symbolic and Neural Commonsense Knowledge Graphs.
Maarten Sap, Ronan Le Bras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A. Smith, and Yejin Choi, ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning.
Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz, and Yejin Choi, COMET: Commonsense Transformers for Automatic Knowledge Graph Construction.