metadata: migrate score_type -> score_pipeline (atomic stage contract; see mm-eval scorer docs/en/SCORING.md)

metadata.json

@@ -1,55 +1,58 @@
 {
- "name": "AI2D",
- "release_date": "2016-08-26",
- "subsets": {
-  "main": {
-   "language": [
-    "en"
-   ],
-   "modalities": [
-    "single_image_start"
-   ],
-   "task_type": "multiple_choice_qa",
-   "score_type": "llm_extract",
-   "score_protocol": {
-    "reference": "vlmevalkit@vlmeval/dataset/image_mcq.py:249-324 (ImageMCQDataset.evaluate_heuristic) -> vlmevalkit@vlmeval/dataset/utils/multiple_choice.py:475-508 mcq_vanilla_eval: can_infer rule prefetch, then GPT extractor (extract_answer_from_item @vlmeval/dataset/utils/multiple_choice.py:359-407) maps verbose output to a letter, rule-compare vs GT; AI2D_TEST registered @vlmeval/dataset/image_mcq.py:100. Cross-check: lmms-eval@lmms_eval/tasks/ai2d/ai2d.yaml:41-55 (MultiChoiceRegexFilter + exact_match, pure rule)",
-    "note": "mm-eval prompt follows the lmms-eval trailer; lmms-eval grades AI2D with deterministic regex extraction only, VLMEvalKit adds the GPT extraction fallback. Both are plain per-sample accuracy — no aggregation caveat."
-   },
-   "prompt_template": "<image>{{ question }}\n{% for k, v in options.items() %}{{ k }}. {{ v }}\n{% endfor %}Answer with the option's letter from the given choices directly.",
-   "mapping_from_source": {
-    "media": {
-     "from": "image",
-     "type": "list",
-     "min_items": 1,
-     "max_items": 1
-    },
-    "id": {
-     "from": "id"
-    },
-    "question": {
-     "from": "question"
-    },
-    "answer": {
-     "from": "answer",
-     "optional": true
-    },
-    "options": {
-     "from": "options",
-     "optional": true,
-     "note": "list source values are normalized to {A,B,...} dict"
-    },
-    "source": {
-     "format": "huggingface",
-     "url": {
-      "test": "https://huggingface.co/datasets/lmms-lab/ai2d"
-     }
+  "name": "AI2D",
+  "release_date": "2016-08-26",
+  "subsets": {
+    "main": {
+      "language": [
+        "en"
+      ],
+      "modalities": [
+        "single_image_start"
+      ],
+      "task_type": "multiple_choice_qa",
+      "score_pipeline": [
+        "rule-match",
+        "llm-match"
+      ],
+      "score_protocol": {
+        "reference": "vlmevalkit@vlmeval/dataset/image_mcq.py:249-324 (ImageMCQDataset.evaluate_heuristic) -> vlmevalkit@vlmeval/dataset/utils/multiple_choice.py:475-508 mcq_vanilla_eval: can_infer rule prefetch, then GPT extractor (extract_answer_from_item @vlmeval/dataset/utils/multiple_choice.py:359-407) maps verbose output to a letter, rule-compare vs GT; AI2D_TEST registered @vlmeval/dataset/image_mcq.py:100. Cross-check: lmms-eval@lmms_eval/tasks/ai2d/ai2d.yaml:41-55 (MultiChoiceRegexFilter + exact_match, pure rule)",
+        "note": "mm-eval prompt follows the lmms-eval trailer; lmms-eval grades AI2D with deterministic regex extraction only, VLMEvalKit adds the GPT extraction fallback. Both are plain per-sample accuracy — no aggregation caveat."
+      },
+      "prompt_template": "<image>{{ question }}\n{% for k, v in options.items() %}{{ k }}. {{ v }}\n{% endfor %}Answer with the option's letter from the given choices directly.",
+      "mapping_from_source": {
+        "media": {
+          "from": "image",
+          "type": "list",
+          "min_items": 1,
+          "max_items": 1
+        },
+        "id": {
+          "from": "id"
+        },
+        "question": {
+          "from": "question"
+        },
+        "answer": {
+          "from": "answer",
+          "optional": true
+        },
+        "options": {
+          "from": "options",
+          "optional": true,
+          "note": "list source values are normalized to {A,B,...} dict"
+        },
+        "source": {
+          "format": "huggingface",
+          "url": {
+            "test": "https://huggingface.co/datasets/lmms-lab/ai2d"
+          }
+        }
+      },
+      "prompt_template_source": {
+        "origin": "official",
+        "reference": "https://github.com/EvolvingLMMs-Lab/lmms-eval/blob/main/lmms_eval/tasks/ai2d/utils.py (ai2d_doc_to_text — 'A./B./...' options + 'Answer with the option's letter from the given choices directly.' canonical trailer)",
+        "notes": "Tier 4: lmms-eval AI2D canonical evaluation prompt."
+      }
     }
-   },
-   "prompt_template_source": {
-    "origin": "official",
-    "reference": "https://github.com/EvolvingLMMs-Lab/lmms-eval/blob/main/lmms_eval/tasks/ai2d/utils.py (ai2d_doc_to_text — 'A./B./...' options + 'Answer with the option's letter from the given choices directly.' canonical trailer)",
-    "notes": "Tier 4: lmms-eval AI2D canonical evaluation prompt."
-   }
   }
- }
-}
+}