| # MC Taco | |
| ### Paper | |
| Title: `"Going on a vacation" takes longer than "Going for a walk": A Study of Temporal Commonsense Understanding` | |
| Abstract: https://arxiv.org/abs/1909.03065 | |
| MC-TACO is a dataset of 13k question-answer pairs that require temporal commonsense | |
| comprehension. The dataset contains five temporal properties, (1) duration (how long | |
| an event takes), (2) temporal ordering (typical order of events), (3) typical time | |
| (when an event occurs), (4) frequency (how often an event occurs), and (5) stationarity | |
| (whether a state is maintained for a very long time or indefinitely). | |
| WARNING: Running this task with a `--limit` arg will give misleading results! The | |
| corresponding dataset is structured such that each multiple-choice-question gathered | |
| by the authors is split into question-option pairs, where each such pair gets | |
| siloed into an individual document for plausibility testing. Because the harness | |
| shuffles these documents, setting `--limit` will likely "cut off" certain candidate | |
| answers. This is a problem because the task's metrics require an exhaustive evaluation | |
| of a question's options. See section 4 of the paper for details. | |
| Homepage: https://leaderboard.allenai.org/mctaco/submissions/public | |
| ### Citation | |
| ``` | |
| BibTeX-formatted citation goes here | |
| ``` | |
| ### Groups and Tasks | |
| #### Groups | |
| * Not part of a group yet. | |
| #### Tasks | |
| * `mc_taco` | |
| ### Checklist | |
| For adding novel benchmarks/datasets to the library: | |
| * [ ] Is the task an existing benchmark in the literature? | |
| * [ ] Have you referenced the original paper that introduced the task? | |
| * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? | |
| If other tasks on this dataset are already supported: | |
| * [ ] Is the "Main" variant of this task clearly denoted? | |
| * [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? | |
| * [ ] Have you noted which, if any, published evaluation setups are matched by this variant? | |