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README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - visual-question-answering
+language:
+  - en
+tags:
+  - spatial-reasoning
+  - map-understanding
+  - multi-choice-qa
+configs:
+  - config_name: t1_direct
+    data_files:
+      - split: test
+        path: data/t1_direct.jsonl
+  - config_name: t1_oracle
+    data_files:
+      - split: test
+        path: data/t1_oracle.jsonl
+  - config_name: t2_direct
+    data_files:
+      - split: test
+        path: data/t2_direct.jsonl
+  - config_name: t2_oracle
+    data_files:
+      - split: test
+        path: data/t2_oracle.jsonl
+  - config_name: t3_direct
+    data_files:
+      - split: test
+        path: data/t3_direct.jsonl
+  - config_name: t3_oracle
+    data_files:
+      - split: test
+        path: data/t3_oracle.jsonl
+  - config_name: t4_direct
+    data_files:
+      - split: test
+        path: data/t4_direct.jsonl
+  - config_name: t4_oracle
+    data_files:
+      - split: test
+        path: data/t4_oracle.jsonl
+---
+
+# Map-based Spatial Reasoning Benchmark
+
+A multi-view map-based spatial reasoning benchmark. Each row is one multiple-choice
+question instance over a registered map image; models must answer with a single option
+letter. Four tasks (T1–T4), four base-map views, and controlled evidence conditions
+(direct / oracle) and world perturbations (transform / world layers) allow fine-grained
+analysis of spatial reasoning robustness.
+
+## Task overview
+
+| Task | Question type | Description |
+|---|---|---|
+| T1 | direction / angular_order / egocentric_side / dual_anchor_direction | Cardinal direction, clockwise angular ordering, and egocentric side between colored point markers |
+| T2 | composite_euclidean_distance / distance ranking | Comparing metric distances between marked points |
+| T3 | segment_building_count (subtasks: `route`, `seg`) | Counting first-row buildings along a directed route segment |
+| T4 | waypoint_ordering | Ordering of waypoints along a route |
+
+## Sample counts (per condition)
+
+`direct` and `oracle` contain the same number of rows (65,200 in total = 32,600 x 2).
+
+### T1 — 10,000
+
+Base question set = 400 instances per view. 7 geometric transform variants (rot90,
+rot180, rot270, mirror_h, mirror_h_rot90/180/270) replicate the base set.
+
+| view | composition | rows |
+|---|---|---|
+| sat | base 400 + 7 transforms x 400 | 3,200 |
+| wprd01 | base 400 + 7 transforms x 400 | 3,200 |
+| blank | base 400 + 7 transforms x 400 | 3,200 |
+| webrd04 | base 400 only | 400 |
+| **total** | | **10,000** |
+
+### T2 — 10,000
+
+Same structure as T1 (400 base instances, same view/transform coverage): 3,200 x 3 + 400 = **10,000**.
+
+### T3 — 4,600
+
+Base question set = 200 instances per view; world layer has 2 variants
+(`intervention_001`, `sham_001`) with 200 each. The `blank` view is not used for T3:
+the task is building-footprint recognition, which is only meaningful on imagery that
+actually shows buildings (satellite / map tiles).
+
+| view | composition | rows |
+|---|---|---|
+| sat | base 200 + 7 transforms x 200 + 2 world x 200 | 2,000 |
+| wprd01 | base 200 + 7 transforms x 200 + 2 world x 200 | 2,000 |
+| webrd04 | base 200 + 2 world x 200 | 600 |
+| **total** | | **4,600** |
+
+### T4 — 8,000
+
+Base question set = 400 instances; world layer = 2 variants x 200. The `blank` view is
+not used for T4: the task is road/waypoint recognition on the route network, which
+requires imagery that actually depicts roads (satellite / map tiles).
+
+| view | composition | rows |
+|---|---|---|
+| sat | base 400 + 7 transforms x 400 + 2 world x 200 | 3,600 |
+| wprd01 | base 400 + 7 transforms x 400 + 2 world x 200 | 3,600 |
+| webrd04 | base 400 + 2 world x 200 | 800 |
+| **total** | | **8,000** |
+
+## Dimensions
+
+| Field | Values | Meaning |
+|---|---|---|
+| `view` | `sat` / `webrd04` / `wprd01` / `blank` | Base map style: satellite imagery / road map / place-label map / blank background. **Note:** the `webrd04` (road-map) view is only provided for the `base` layer — its tiles contain textual labels (e.g., Chinese characters), which would become unreadable or mirrored after rotation/flipping, so no `transform` variants are generated for this view |
+| `layer` | `base` / `transform` / `world` | Original scene, geometric transform stress test, or world intervention |
+| `variant` | `rot90`, `rot180`, `rot270`, `mirror_h`, `mirror_h_rot*` (transform); `intervention_001`, `sham_001` (world); `null` (base) | Sub-variant of the layer. Note: transform variants have rotated/flipped map frames — "north is up" applies to the transformed image |
+| `condition` | `direct` / `oracle` | `oracle` overlays explicit task annotations (e.g., route segments, measured rays); `direct` does not |
+
+## Row schema
+
+```json
+{
+  "id": "e5f31604234e_sat_oracle",
+  "task_id": "T1",
+  "layer": "base",
+  "variant": null,
+  "view": "sat",
+  "condition": "oracle",
+  "question_type": "angular_order",
+  "question": "From the green point, sweeping clockwise from north, ...",
+  "options": ["A. yellow, red", "B. red, yellow"],
+  "answer": "B",
+  "answer_letter": "B",
+  "system_prompt": "You are evaluating spatial reasoning ...",
+  "images": ["images/t1/c_06d46000d7/s_429d01__q_e5ebc72207__base__oracle__sat_oracle_q4.png"],
+  "meta": {
+    "case_id": "c_06d46000d7",
+    "scheme": "s_429d01",
+    "instance_id": "q_e5ebc72207",
+    "tile_type": "sat",
+    "subtask": null
+  }
+}
+```
+
+- `options` are pre-shuffled; the correct letter is `answer_letter`.
+- Evaluation is exact match on the option letter for all rows.
+- Multiple-choice prompt format: append `Options:\n<options>` and instruct the model to
+  output only the letter (see `system_prompt`).
+
+## Image naming
+
+Images live under `images/{task}/{case_code}/`. Directory segments `case_id`, `scheme`
+and `question_dir` are anonymized with deterministic short codes (`c_*`, `s_*`, `q_*`);
+the remaining segments (`layer`, `condition`, original file name) are kept verbatim, e.g.
+
+```
+images/t1/c_06d46000d7/s_429d01__q_e5ebc72207__base__oracle__sat_oracle_q4.png
+```
+
+The same source image may be referenced by several rows (e.g., shared across transform
+variants or views); 65,200 rows reference 20,200 unique image files.
+
+## Loading
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("<repo_id>", "t1_oracle", split="test")
+row = ds[0]
+img = Image.open(row["images"][0])  # or load from the local repo root
+```
+
+## Anonymization note
+
+Identifiers of the source map data (case / scheme / question directory) are replaced by
+deterministic hash codes and are not reversible from this repository.