A 51-pair BIG-bench task that asks which of two English events caused the other, scored as two-way multiple choice under three prompt formats.
unassessed
| Category | reasoning |
|---|---|
| Subcategory | BIG-bench two-event causal commonsense (51 pairs, three promptings) |
| Page status | unknown |
| Metric | multiple_choice_grade |
| Direction | higher_is_better |
| Unit | % |
| Dataset size | 153 |
| Dataset licence | Apache-2.0 |
| Publisher | Google (BIG-bench collaboration) |
cause_and_effect gives two short English events and asks which one caused the other. Guy Gur-Ari and Neta Krakover wrote about fifty such pairs (51 in each JSON file). Unlike SuperGLUE COPA, there is no separate premise: the model sees only the two events. The skill is everyday causal direction, not COPA's three-sentence plausibility setup and not BBH causal_judgement.
Two-option multiple choice, preferred metric multiple_choice_grade. Three subtasks share the same pairs: two_sentences (pick the causing event), one_sentence (pick the more likely "because" sentence), and one_sentence_no_prompt (compare the two "because" strings with an empty context; append_choices_to_input is false). Canary GUID embedded.
No model card in ModelSpec reports this benchmark yet.