360 SVG path strings labelled with a shape name; BIG-bench scores multiple_choice_grade, and BBH keeps a 250-item slice.
unassessed
| Category | reasoning |
|---|---|
| Subcategory | name a polygon from an SVG path string (BIG-bench / BBH) |
| Page status | unknown |
| Metric | multiple_choice_grade |
| Direction | higher_is_better |
| Unit | % |
| Dataset size | 360 |
| Dataset licence | Apache-2.0 |
| Publisher | Google (BIG-bench collaboration) |
geometric_shapes shows an SVG path `d` string on a 100×100 canvas and asks which simple shape it draws. Author Zijie J. Wang wrote the paths to test whether a language model can parse move/line commands and name the geometry, without a raster image. task.json has ten gold labels with 36 items each: line, triangle, rectangle, kite, pentagon, hexagon, heptagon, octagon, circle, sector. Trapezoid and ellipse appear only as extra option keys on some items, not as gold classes. English names; the input is path syntax, not pixels. [BIG-Bench Hard](bbh.md) keeps 250 of these items.
Multiple choice with preferred metric multiple_choice_grade; metrics also list rouge, bleu, and exact_str_match. append_choices_to_input is true. 288 items have 10 options and 72 have 11. Canary GUID embedded. The auto-generated README header reports 359 multiple-choice and 359 free-text dummy queries; hails/bigbench geometric_shapes_zero_shot default is also 359.
No model card in ModelSpec reports this benchmark yet.