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README.md

@@ -35,34 +35,27 @@ SpatialWorld is a comprehensive benchmark designed to evaluate spatial reasoning
 
 ## 📊 Dataset Statistics
 
-This Hugging Face repository contains 630 unified tasks:
+This Hugging Face repository contains the complete **SpatialWorld Benchmark** with all 630 tasks:
 
-| Platform | Tasks | Task Types |
-|----------|-------|------------|
-| AI2Thor | 343 | Object manipulation, navigation |
-| CARLA | 80 | Urban navigation, traffic scenarios |
-| ProcTHOR | 127 | Indoor navigation, household tasks |
-| VirtualHome | 80 | Multi-agent household activities |
-| **Total** | **630** | Multi-platform spatial reasoning |
+| Platform | Tasks | Task Types | Unique Fields |
+|----------|-------|------------|---------------|
+| AI2Thor | 343 | Object manipulation, navigation | Category, Evaluation_Type, Level |
+| CARLA | 80 | Urban navigation, traffic scenarios | executor, image_url, input_modality, origin_location, weather |
+| ProcTHOR | 127 | Indoor navigation, household tasks | scene_index, Category, Evaluation_Type, Level |
+| VirtualHome | 80 | Multi-agent household activities | executor, image_url, input_modality, origin_location, weather |
+| **Total** | **630** | Multi-platform spatial reasoning | **20 fields total** |
 
 ## 🗂️ Repository Structure
 
 ```
-benchmark/            # Full benchmark data with original JSON structures
-├── ai2thor/
-├── carla/
-├── procthor/
-├── virtualhome/
-├── embodiedcity/
-├── game/
-└── shared/
-
-data/                 # Unified Hugging Face dataset
-├── spatialworld_unified.jsonl     # 630 tasks in unified schema
-└── spatialworld_samples.parquet  # Sample for quick preview
+spatialworld.jsonl    # Full dataset (630 tasks, 20 columns)
+README.md             # This file
 ```
 
-The Hugging Face dataset (`spatialworld_unified.jsonl`) provides a unified schema across all platforms. Original platform-specific JSON files remain in `benchmark/` for reference.
+The `spatialworld.jsonl` file contains **all 630 tasks** with **all original fields** from every platform. Schema differences are handled by:
+- Including all 20 possible fields as top-level columns
+- Using `null` for fields that don't exist in a particular platform
+- Encoding complex nested structures (`golden_actions`, `success_conditions`, `target_object_types`) as JSON strings
 
 ## 🎮 Unified Action Space
 
@@ -117,23 +110,52 @@ Each task contains:
 
 ```python
 from datasets import load_dataset
+import json
 
-# Load the unified dataset (all 630 tasks from all platforms)
+# Load the full dataset (all 630 tasks, all 20 fields)
 dataset = load_dataset("Spatialworld/Spatialworld-bench", split="train")
 
-# Access a task
+# Access a task - all fields are available
 task = dataset[0]
-print(task["task_id"])           # e.g., "ai2thor00000"
-print(task["platform"])         # e.g., "ai2thor"
-print(task["instruction"])
-
-# Parse JSON fields
-import json
-golden_actions = json.loads(task["golden_actions_json"])
-success_conditions = json.loads(task["success_conditions_json"])
-platform_specific = json.loads(task["platform_specific_json"])
+print(f"Task: {task['task_id']} ({task['platform']})")
+print(f"Instruction: {task['instruction']}")
+print(f"Scene: {task['scene']}")
+
+# Parse JSON-encoded fields
+golden_actions = json.loads(task["golden_actions"])
+success_conditions = json.loads(task["success_conditions"])
+target_objects = json.loads(task["target_object_types"])
+
+# Platform-specific fields (null if not applicable)
+print(f"Category: {task['Category']}")  # Only for ai2thor/procthor
+print(f"Executor: {task['executor']}")   # Only for carla/virtualhome
 ```
 
+### Dataset Schema
+
+| Field | Type | Description | Platforms |
+|-------|------|-------------|-----------|
+| `task_id` | string | Unique identifier | All |
+| `task_name` | string | Human-readable name | All |
+| `platform` | string | Platform name | All |
+| `instruction` | string | Natural language instruction | All |
+| `scene` | string | Scene identifier | ai2thor, carla, virtualhome |
+| `max_steps` | int | Maximum steps | All |
+| `golden_actions` | string (JSON) | Action sequence | All |
+| `success_conditions` | string (JSON) | Success criteria | All |
+| `target_object_types` | string (JSON) | Target objects | ai2thor, procthor |
+| `success_logic` | string | AND/OR logic | ai2thor, procthor |
+| `target_description` | string | Detailed description | ai2thor, procthor |
+| `Category` | string | Task category | ai2thor, procthor |
+| `Evaluation_Type` | string | Evaluation type | ai2thor, procthor |
+| `Level` | string | Difficulty level | ai2thor, procthor |
+| `executor` | string | Executor type | carla, virtualhome |
+| `image_url` | string | Image path | carla, virtualhome |
+| `input_modality` | string | Input type | carla, virtualhome |
+| `origin_location` | bool | Origin flag | carla, virtualhome |
+| `scene_index` | int | Scene number | procthor |
+| `weather` | string | Weather condition | carla, virtualhome |
+
 ### Loading Original Tasks (Local)
 
 For full benchmark with original JSON structures: