Image
Caption

A medium-long shot of green water flowing through an area that has two rock and dirt hillsides along the sides of it. Along the dirt hillsides, there are tire tracks that run horizontally. To the left of the water and on the hillside, a gray tube can be seen. Covering the tube is the dirt hill. Sticking out of the hillside on the near side of the river is another tube that can barely be seen. On the river, the reflection of the blue sky and trees. On the other side of the hillside, on the left, there are multiple trees and a cut-grass field. On the grass and along its center, there is an orange umbrella. It is daytime, as the sun is shining brightly in the area.

Scene Graph
    Scene Graph
QA + verification programs
Q: What is flowing in the scene, and what color is it?
A: The water is flowing in the scene, and it is green in color.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'water' in entity:                                               
  3             if 'flow' in scene_graph.get_attributes(entity).get('state',    
    ''):                                                                        
  4                 return scene_graph.get_attributes(entity).get('color', '')  
  5     return None                                                             
  6                                                                             

gpt-4o: In the scene, water is flowing through a small channel or ditch. The water appears to be a murky greenish color.
hscore: 96.95%
• <state (water, flowing)> == <state (water, flowing)> (100.0%)
• <whole (water)> == <whole (water)> (100.0%)
• <color (water, green)> == <color (water, greenish)"> (90.0%)
tscore: 87.61%
• <whole (water)> == <whole (water)> (100.0%)
• <state (water, flowing)> == <state (water, flow)> (90.0%)
• <color (water, greenish)"> == <color (water, green)> (90.0%)

Q: How many hillsides are present in the scene, and what texture do they have?
A: There are two hillsides in the scene, and they have a rock and dirt texture.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'hillsides' in entity:                                           
  3             count = scene_graph.get_attributes(entity).get('count', '0')    
  4             texture = scene_graph.get_attributes(entity).get('texture', '') 
  5             return f'There are {count} hillsides with a {texture} texture.' 
  6     return None                                                             
  7                                                                             

gpt-4o: The scene shows two hillsides, one on each side of a small water channel. The texture of the hillsides appears to be rough and uneven, with visible tracks or grooves, likely from construction or landscaping equipment. The ground looks dry and consists of dirt or soil.
hscore: 92.62%
• <whole (hillsides)> == <whole (hillsides)> (100.0%)
• <count (hillsides, ==2)> == <count (hillsides, ==2)> (100.0%)
• <state (hillsides, rock and dirt texture)> == <state (hillsides, uneven)> (80.0%)
tscore: 81.85%
• <whole (hillsides)> == <whole (hillsides)> (100.0%)
• <count (hillsides, ==2)> == <count (hillsides, ==2)> (100.0%)
• <spatial (hillsides, water channel, on each side of)> == <spatial (hillsides, water, along the sides of)> (90.0%)

Q: What is the state of the tire tracks found in the scene?
A: The tire tracks run horizontally along the hillsides.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'tire tracks' in entity:                                         
  3             return scene_graph.get_attributes(entity).get('state', '')      
  4     return None                                                             
  5                                                                             

gpt-4o: The tire tracks in the scene appear to be relatively fresh and well-defined. They are visible across the dirt surface, indicating that a vehicle has recently driven over the area. The tracks are parallel and consistent, suggesting that the ground is firm enough to hold the impressions clearly. There is no significant erosion or disturbance around the tracks, which implies that there hasn't been much recent activity or weather events that could have altered their appearance.
hscore: 88.08%
• <state (tire tracks, horizontal)> == <state (tire tracks, parallel)> (80.0%)
• <spatial (tire tracks, hillsides, along)> == <spatial (tire tracks, erosion, no)> (80.0%)
tscore: 78.99%
• <spatial (tire tracks, dirt surface, across)> == <spatial (tire tracks, hillsides, on)> (80.0%)
• <spatial (tire tracks, erosion, no)> == <spatial (tire tracks, hillsides, on)> (80.0%)
• <part (tire tracks)> == <whole (tire tracks)> (80.0%)

Q: What is located to the left of the water in the scene?
A: A gray tube is located to the left of the water.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'tube' in entity:                                                
  3             relations = scene_graph.get_outgoing_relations(entity)          
  4             if 'water' in relations and 'left of' in                        
    relations['water'].get('spatial', ''):                                      
  5                 return f'A gray tube is located to the left of the water.'  
  6     return None                                                             
  7                                                                             

gpt-4o: To the left of the water in the scene, there is a drainage pipe embedded in the ground. The area around the pipe and the water appears to be a dirt or gravel surface, possibly part of a construction or landscaping project. In the background, there are trees, a fence, and a structure with a red roof.
hscore: 54.93%
• <spatial (gray tube, water, to the left of)> == <spatial (drainage pipe, water, to the left of)> (70.0%)
• <whole (gray tube)> == <whole (drainage pipe)> (50.0%)
• <color (gray tube, gray)> == <color (structure's roof, red)> (40.0%)
tscore: 76.89%
• <whole (trees)> == <whole (trees)> (100.0%)
• <whole (water)> == <whole (water)> (100.0%)
• <spatial (water, drainage pipe, adjacent to)> == <spatial (tube, river, near side of)> (80.0%)
Image
Caption

An outdoor angled up long shot view taken from the southwest corner of Central Park in New York City. Closer up and towards the left side is a gold statue of a person with one arm raised up, and a gold horse beneath them. The gold statue is on top of a thick and tall cement structure that has designs engraved and embossed onto its surface. To the left of the statue is a partial view of tree branches with green leaves, and to the bottom right of the statue are more partial views of tree branches with green leaves. Far behind the statue, and to the right of it, is a tall beige colored building that is many stories high and appears to be old. Behind the beige building and to the right of it, is an enormous silver colored skyscraper building. As the skyscraper goes up, it gets more narrow until reaching its pointed top. The sky is clear, and is a light blue color that gets slightly darker the higher up it goes.

Scene Graph
    Scene Graph
QA + verification programs
Q: What materials make up the statue and its base in this scene from Central Park?
A: The statue is made of gold, and it sits on top of a cement structure that is thick and tall with engraved and embossed designs.
   0 def execute_command(scene_graph):                                          
   1     statue_entity = None                                                   
   2     cement_entity = None                                                   
   3     for entity in scene_graph.get_entities():                              
   4         if 'statue' in entity:                                             
   5             statue_entity = entity                                         
   6         elif 'cement structure' in entity:                                 
   7             cement_entity = entity                                         
   8     if statue_entity and cement_entity:                                    
   9         statue_material =                                                  
     scene_graph.get_attributes(statue_entity).get('material', '')              
  10         cement_description =                                               
     scene_graph.get_attributes(cement_entity).get('state', '')                 
  11         return f"The statue is made of {statue_material}, and it sits on   
     top of a cement structure that is thick and tall with                      
     {cement_description}."                                                     
  12     return None                                                            
  13                                                                            

gpt-4o: The statue in the scene from Central Park appears to be made of gilded bronze, giving it a golden appearance. The base of the statue is constructed from stone, likely granite or a similar durable material, which is common for such monuments.
hscore: 66.49%
• <whole (statue)> == <whole (statue)> (100.0%)
• <material (statue, gold)> == <material (statue, gilded bronze)> (90.0%)
• <state (cement structure's designs, engraved)> == <state (statue's base, constructed)> (70.0%)
tscore: 83.92%
• <whole (statue)> == <whole (statue)> (100.0%)
• <state (statue, gilded)> == <state (statue, gold)> (90.0%)
• <material (statue, gilded bronze)> == <material (statue, gold)> (90.0%)

Q: Describe the overall architecture details of the buildings seen in the photo.
A: The photo features a tall, beige-colored, old building, and an enormous silver-colored skyscraper with a narrow top.
   0 def execute_command(scene_graph):                                          
   1     building1_entity = None                                                
   2     building2_entity = None                                                
   3     for entity in scene_graph.get_entities():                              
   4         if 'building_1' in entity:                                         
   5             building1_entity = entity                                      
   6         elif 'building_2' in entity:                                       
   7             building2_entity = entity                                      
   8     if building1_entity and building2_entity:                              
   9         building1_attributes = scene_graph.get_attributes(building1_entity)
  10         building2_attributes = scene_graph.get_attributes(building2_entity)
  11         building1_description = f"a tall,                                  
     {building1_attributes.get('color', 'beige')}-colored,                      
     {building1_attributes.get('state', 'old')} building"                       
  12         building2_description = f"an enormous                              
     {building2_attributes.get('color', 'silver')}-colored skyscraper with      
     {building2_attributes.get('shape', 'a narrow top')}"                       
  13         return f"The photo features {building1_description}, and           
     {building2_description}."                                                  
  14     return None                                                            
  15                                                                            

gpt-4o: The photo showcases a mix of architectural styles in an urban setting. Here are the details: 1. **Tall Modern Skyscraper**: - **Design**: The most prominent building in the photo is a very tall, slender skyscraper. It has a sleek, modern design with a glass facade. - **Shape**: The building has a unique, tapering form that narrows as it rises, giving it a distinctive, almost futuristic appearance. - **Materials**: Predominantly glass and steel, contributing to its modern aesthetic. 2. **Mid-20th Century Building**: - **Design**: In the middle ground, there is a building that appears to be from the mid-20th century. It has a more traditional, boxy design compared to the modern skyscraper. - **Features**: The building has a flat roof and a facade with a grid of windows, typical of mid-century architecture. - **Materials**: Likely concrete and stone, with large windows. 3. **Historic Monument**: - **Design**: In the foreground, there is a historic monument featuring a golden statue. The statue depicts a figure on a chariot, which is a classical design element. - **Base**: The base of the monument is made of stone and has detailed carvings and inscriptions, indicative of classical or neoclassical architecture. 4. **Surrounding Elements**: - **Trees**: The presence of trees in the foreground suggests the buildings are near a park or green space. - **Sky**: The clear blue sky provides a stark contrast to the buildings, highlighting their architectural details. Overall, the photo captures a blend of modern and historical architectural elements, showcasing the diversity of urban architecture.
hscore: 77.61%
• <whole (skyscraper)> == <whole (skyscraper)> (100.0%)
• <state (skyscraper, enormous)> == <state (skyscraper, tall)> (90.0%)
• <state (old building, tall)> == <state (skyscraper, tall)> (80.0%)
tscore: 73.54%
• <whole (skyscraper)> == <whole (skyscraper)> (100.0%)
• <type (skyscraper, modern)> == <type (building, skyscraper)> (90.0%)
• <shape (skyscraper, tapering)> == <shape (skyscraper, narrow)> (80.0%)
Image
Caption

A top down 3/4 view of a Warhammer figure from the Age of Sigmar placed on top of a tabletop map meant to resemble a dungeon. The figure resembles a brown Tree Lord and is grasping a scythe with two hands. The figure’s base has fake grass and a brown edge all around. The scythe has a wooden handle made of light brown wood and the blade is green gray. Behind the figure, there is a modular dungeon set. The top and left of the frame has a gray dungeon fence. The upper left frame has a dungeon wall composed of bricks.

Scene Graph
    Scene Graph
QA + verification programs
Q: What does the Warhammer figure from the Age of Sigmar resemble?
A: The Warhammer figure resembles a Tree Lord.
  0 def execute_command(scene_graph):                                           
  1     # Find the Warhammer figure                                             
  2     for entity in scene_graph.get_entities():                               
  3         if 'Warhammer figure' in entity:                                    
  4             part_entities = scene_graph.get_outgoing_relations(entity)      
  5             for part_entity in part_entities:                               
  6                 if 'figure' in part_entity:                                 
  7                     return scene_graph.get_attributes(part_entity)['state'] 
  8     return None                                                             
  9                                                                             

gpt-4o: The Warhammer figure from the Age of Sigmar in the image resembles a creature with a blend of humanoid and tree-like features. It has a body that appears to be made of wood or bark, with branches or antlers extending from its head. The figure is holding a staff or weapon with a curved blade, which has intricate designs on it. The overall appearance suggests it could be a Sylvaneth, a faction in Age of Sigmar known for their forest spirits and tree-like warriors. The setting, with a cracked and barren ground and a gothic-style fence, adds to the dark and mystical atmosphere typical of the Warhammer universe.
hscore: 56.77%
• <whole (figure)> == <whole (Warhammer figure)> (70.0%)
• <type (figure, Warhammer)> == <whole (Warhammer figure)> (60.0%)
• <state (figure, resembles)> == <state (setting, gothic> (50.0%)
tscore: 70.35%
• <whole (Warhammer figure)> == <whole (Warhammer figure)> (100.0%)
• <part (Warhammer figure's body)> == <whole (Warhammer figure)> (80.0%)
• <whole (setting)> == <image> (70.0%)

Q: What elements frame the dungeon in the current scene?
A: The frame includes a gray dungeon fence at the top and left and a dungeon wall to the upper left.
  0 def execute_command(scene_graph):                                           
  1     frame_elements = []                                                     
  2     # Find the fence                                                        
  3     for entity in scene_graph.get_entities():                               
  4         if 'fence' in entity or 'dungeon wall' in entity:                   
  5             for position, spatial_data in                                   
    scene_graph.get_outgoing_relations(entity).items():                         
  6                 if spatial_data['spatial'] == 'in':                         
  7                     frame_elements.append(scene_graph.describe(scene_graph.g
    enerate_subgraph([entity])))                                                
  8     return ', '.join(frame_elements)                                        
  9                                                                             

gpt-4o: The dungeon in the current scene is framed by several elements: 1. **Walls**: The dungeon is enclosed by stone walls, which are visible on the left side of the image. 2. **Fences**: There are metal fences with pointed tops, visible in the background, adding to the dungeon-like atmosphere. 3. **Ground Texture**: The ground has a cracked, rough texture, contributing to the dungeon's rugged and aged appearance. 4. **Gate**: There is a gate visible in the background, which is part of the fencing and adds to the enclosed, dungeon-like feel. These elements together create a confined and eerie environment typical of a dungeon setting.
hscore: 67.1%
• <spatial (dungeon wall, upper left)> == <spatial (walls, left side of the image)> (80.0%)
• <whole (dungeon wall)> == <whole (dungeon)> (80.0%)
• <spatial (dungeon fence, left of the frame)> == <spatial (walls, left side of the image)> (70.0%)
tscore: 71.13%
• <spatial (gate, fencing)> == <spatial (fence, left, in)> (80.0%)
• <whole (dungeon)> == <whole (dungeon wall)> (80.0%)
• <material (walls, stone)> == <material (dungeon wall, bricks)> (80.0%)

Q: What are the handles of the scythe made of?
A: The handles of the scythe are made of wood.
  0 def execute_command(scene_graph):                                           
  1     # Find the scythe's handle                                              
  2     for entity in scene_graph.get_entities():                               
  3         if "scythe's handle" in entity:                                     
  4             return scene_graph.get_attributes(entity)['material']           
  5     return None                                                             
  6                                                                             

gpt-4o: The handles of the scythe in the image appear to be made of wood, resembling branches or twigs. The design is consistent with the natural, organic aesthetic of the figure holding it.
hscore: 92.08%
• <material (scythe's handles, wood)> == <material (scythe's handles, wood)> (100.0%)
• <part (scythe)> == <part (scythe's handles)> (80.0%)
tscore: 83.99%
• <material (scythe's handles, wood)> == <material (scythe's handle, wood)> (90.0%)
• <part (scythe's handles)> == <part (scythe's handle)> (90.0%)
• <part (figure)> == <part (figure's base)> (80.0%)

Q: What is the significance of the traits attributed to the tabletop map?
A: The traits signify the tabletop map as a representation of a dungeon.
  0 def execute_command(scene_graph):                                           
  1     # Find the tabletop map                                                 
  2     for entity in scene_graph.get_entities():                               
  3         if 'tabletop map' in entity:                                        
  4             return                                                          
    scene_graph.describe(scene_graph.generate_subgraph([entity]))               
  5     return None                                                             
  6                                                                             

gpt-4o: The tabletop map in the image is designed for miniature wargaming, a type of strategy game where players use miniature figures to represent units on a battlefield. The significance of the traits attributed to the map can be broken down into several key aspects: 1. **Terrain Features**: The map includes various terrain features such as walls, gates, and ground textures. These elements are crucial for gameplay as they can provide cover, block line of sight, and affect movement. For example, walls and gates can serve as obstacles that units must navigate around or through, adding strategic depth to the game. 2. **Aesthetic Appeal**: The detailed and thematic design of the map enhances the visual appeal of the game. The cracked ground, weathered walls, and other intricate details contribute to the immersive experience, making the game more engaging for players. 3. **Gameplay Mechanics**: The specific layout and features of the map can influence the tactics and strategies used by players. For instance, the placement of obstacles and open spaces can dictate the flow of battle, encouraging players to think critically about positioning and movement. 4. **Thematic Consistency**: The map's design often reflects the setting or theme of the game. In this case, the dark, gothic elements suggest a fantasy or horror theme, which aligns with the appearance of the miniature figure. This consistency helps to create a cohesive narrative and atmosphere for the game. 5. **Scale and Proportion**: The map is scaled to match the size of the miniatures, ensuring that distances and measurements used in gameplay are accurate. This is important for maintaining balance and fairness in the game. Overall, the traits attributed to the tabletop map play a significant role in enhancing the strategic, aesthetic, and thematic aspects of the miniature wargaming experience.
hscore: 55.9%
• <type (tabletop map, dungeon)> == <type (terrain features, walls)> (60.0%)
• <representational (tabletop map, dungeon, as a representation of)> == <whole (tabletop map)> (50.0%)
tscore: 62.3%
• <whole (tabletop map)> == <whole (tabletop map)> (100.0%)
• <part (gameplay mechanics)> == <image> (70.0%)
• <part (scale and proportion)> == <image> (70.0%)
Image
Caption

A nighttime view up at the Austin skyline with a large firework exploding over it on the left. The firework is spherical explosion of red, white, and pink. It's filling the top left quadrant of the frame. To the right of the firework the prominent building is the Austin Google "Sail" tower. The tower is still under construction in this image with a crane still sticking up skyward on its right side. Beneath the firework smoke from the explosion is drifting down and to the bottom left corner.

Scene Graph
    Scene Graph
QA + verification programs
Q: What shape is the firework in the top left quadrant of the image?
A: The firework in the top left quadrant is spherical in shape.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'firework' in entity:                                            
  3             return scene_graph.get_attributes(entity).get('shape', '')      
  4     return None                                                             
  5                                                                             

gpt-4o: The firework in the top left quadrant of the image is in a circular shape, with bright streaks radiating outward from the center.
hscore: 92.74%
• <shape (firework, spherical)> == <shape (firework, circular)> (90.0%)
• <spatial (firework, top left quadrant, in)> == <spatial (firework, image, top left quadrant, in)> (90.0%)
tscore: 82.4%
• <whole (firework)> == <whole (firework)> (100.0%)
• <shape (firework, circular)> == <shape (firework, spherical)> (90.0%)
• <spatial (firework, image, top left quadrant, in)> == <spatial (firework, building, to the right of)> (80.0%)
Image
Caption

A monster truck is in the air and jumping over a line of red crushed cars. The truck has a color scheme of red and blue. The word "BIG FOOT" is written on the side of the truck in big white letters. The grille of the truck is silver. An orange truck with black stripes is in the background behind the truck red and blue truck. The word "Hot Wheels" is inside a flame logo on the blue wall. The "H" is partially covered by the truck's shark fin design. An orange van is partially cut off from the right of the image next to a crushed blue car. An audience of people are in the background in the stands watching the trucks.

Scene Graph
    Scene Graph
QA + verification programs
Q: Which truck is behind the red and blue truck?
A: The orange truck with black stripes is behind the red and blue truck.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'truck' in entity:                                               
  3             relations = scene_graph.get_outgoing_relations(entity)          
  4             for relation, details in relations.items():                     
  5                 if "red and blue" in                                        
    scene_graph.get_attributes(relation).get('color', "") and 'behind' in       
    details.get('spatial', ""):                                                 
  6                     return scene_graph.get_attributes(entity).get('color',  
    "")                                                                         
  7     return None                                                             

gpt-4o: The truck behind the red and blue truck is an orange and black truck with a tiger-like design.
hscore: 89.73%
• <color (red and blue truck, blue)> == <color (red and blue truck, blue)> (100.0%)
• <color (red and blue truck, red)> == <color (red and blue truck, red)> (100.0%)
• <state (orange truck, has black stripes)> == <state (orange and black truck, behind)> (90.0%)
tscore: 84.99%
• <color (red and blue truck, red)> == <color (truck, red and blue)> (90.0%)
• <color (orange and black truck, black)> == <color (truck, orange)> (90.0%)
• <color (red and blue truck, blue)> == <color (truck, red and blue)> (90.0%)

Q: What design feature is partially covered by the truck?
A: The blue wall's "H" is partially covered by the truck's shark fin design.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if "H" in entity:                                                   
  3             relations = scene_graph.get_outgoing_relations(entity)          
  4             for relation, details in relations.items():                     
  5                 if "shark fin design" in relation and "partially covered by"
    in details.get('spatial', ""):                                              
  6                     return 'The "H" is partially covered by the truck’s     
    shark fin design.'                                                          
  7     return None                                                             

gpt-4o: The truck in the image is partially covering a Hot Wheels logo on the blue banner in the background.
hscore: 55.62%
• <spatial (truck's shark fin design, wall's text, over)> == <spatial (truck, Hot Wheels logo, covering)> (70.0%)
• <color (wall, blue)> == <color (blue banner, blue)> (70.0%)
• <whole (wall)> == <whole (truck)> (60.0%)
tscore: 73.54%
• <whole (truck)> == <whole (truck)> (100.0%)
• <spatial (truck, Hot Wheels logo, covering)> == <image> (70.0%)
• <color (blue banner, blue)> == <image> (70.0%)
Image
Caption

A top-down, close-up of a black and white tabby cat sitting in a round, tall, rattan decorative basket with two stuffed animals. The cat is in the front side of the basket facing forward, angled to the left, with a white stuffed plush bear to the back right and a gray stuffed plush tiger to the back left. The black and white tabby cat is mostly white, with black on top of its head and ears and around the right eye. The iris of the eye is thin and yellow-green, with a large black pupil. The basket has handles. One is in the top right corner, and one is on the left side. The background is a white panel wall with white trim at the bottom. Similar-type baskets are slightly visible on the bottom left and top right. A shadow is visible on the wall behind the basket. Indoors. The lights are on.

Scene Graph
    Scene Graph
QA + verification programs
Q: What is the color pattern of the tabby cat sitting in the basket?
A: The tabby cat is mostly white with black on top of its head, ears, and around the right eye.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'cat' in entity:                                                 
  3             color = scene_graph.get_attributes(entity).get('color', '')     
  4             return color                                                    
  5     return None                                                             
  6                                                                             

gpt-4o: The tabby cat in the basket has a gray and white striped pattern.
hscore: 75.13%
• <color (tabby cat, mostly white)> == <color (cat, tabby)> (80.0%)
• <whole (tabby cat)> == <whole (cat)> (80.0%)
• <color (tabby cat, black)> == <color (cat, tabby)> (80.0%)
tscore: 82.23%
• <whole (cat)> == <whole (cat)> (100.0%)
• <color (cat's fur, gray and white)"> == <color (cat, mostly white)> (80.0%)
• <color (cat, tabby)> == <color (cat, black and white)> (80.0%)

Q: Where is the gray stuffed plush tiger located in relation to the basket?
A: The gray stuffed plush tiger is located at the back left of the basket.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'tiger' in entity:                                               
  3             relations = scene_graph.get_outgoing_relations(entity)          
  4             basket_relation = relations.get('basket', {}).get('spatial', '')
  5             if 'back left' in basket_relation:                              
  6                 return basket_relation                                      
  7     return None                                                             
  8                                                                             

gpt-4o: The gray stuffed plush tiger is located inside the basket, positioned towards the left side.
hscore: 79.47%
• <state (tiger, stuffed plush)> == <state (stuffed plush tiger, gray)> (90.0%)
• <whole (tiger)> == <whole (stuffed plush tiger)> (70.0%)
• <spatial (tiger, basket, at the back left of)> == <spatial (stuffed plush tiger, basket, towards the left side)"> (70.0%)
tscore: 84.62%
• <whole (basket)> == <whole (basket)> (100.0%)
• <type (stuffed plush tiger, plush)> == <type (tiger, stuffed plush)> (90.0%)
• <spatial (stuffed plush tiger, basket, inside)> == <spatial (stuffed animals, basket, in)> (80.0%)

Q: Is the setting indoors or outdoors?
A: The setting is indoors.
  0 def execute_command(scene_graph):                                           
  1     if 'lights' in scene_graph.get_entities():                              
  2         state = scene_graph.get_attributes('lights').get('state', '')       
  3         if 'on' in state:                                                   
  4             return 'indoors'                                                
  5     return 'unknown'                                                        
  6                                                                             

gpt-4o: The setting appears to be indoors. The presence of a wicker basket, stuffed animals, and what looks like a wall in the background suggests an indoor environment.
hscore: 36.21%
• <state (building, indoors)> == <spatial (scene, indoors)> (50.0%)
• <whole (building)> == <whole (stuffed animals)> (50.0%)
• <color (building, red)> == <spatial (scene, indoors)> (40.0%)
tscore: 87.7%
• <whole (stuffed animals)> == <whole (stuffed animals)> (100.0%)
• <spatial (stuffed animals, wicker basket, with)> == <spatial (stuffed animals, basket, in)> (90.0%)
• <whole (wicker basket)> == <whole (basket)> (80.0%)

Q: What material is the basket made of?
A: The basket is made of rattan.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'basket' in entity:                                              
  3             material = scene_graph.get_attributes(entity).get('material',   
    '')                                                                         
  4             return material                                                 
  5     return None                                                             
  6                                                                             

gpt-4o: The basket appears to be made of woven rattan or wicker. This material is commonly used for baskets due to its durability and natural aesthetic.
hscore: 100%
• <material (basket, rattan)> == <material (basket, rattan)> (100.0%)
tscore: 74.96%
• <material (basket, rattan)> == <material (basket, rattan)> (100.0%)
• <whole (basket)> == <whole (basket)> (100.0%)
• <material (basket, wicker)> == <image> (70.0%)
Image
Caption

An outdoor top-down view of a gray brick pathway with an inlaid small metal manhole cover with the letters,"A / W W" debossed in the center of the lid. The text and the lid are rotated about 45 degrees to the right. The bricks of the pathway are laid in a running pattern. A light shadow is covering the upper left half of the manhole cover and the brick pathway, as the sunlight appears and shines in the lower right corner.

Scene Graph
    Scene Graph
QA + verification programs
Q: Describe how the bricks are arranged on the pathway.
A: The bricks are laid in a running pattern.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'bricks' in entity:                                              
  3             return scene_graph.get_attributes(entity).get('state', '')      
  4     return None                                                             
  5                                                                             

gpt-4o: The bricks on the pathway are arranged in a staggered pattern. Each row of bricks is offset from the adjacent rows, creating a running bond pattern. This arrangement provides a visually appealing and structurally stable surface. In the center of the image, there is a circular manhole cover with the letters "W" and "A" inscribed on it. The bricks are laid out uniformly around the manhole cover, maintaining the staggered pattern.
hscore: 77.61%
• <state (bricks, laid in a running pattern)> == <state (bricks, uniform)> (70.0%)
tscore: 80.13%
• <whole (pathway)> == <whole (pathway)> (100.0%)
• <text rendering (manhole cover, \"W\" and \"A\")> == <text rendering (manhole cover, "A / W W")> (90.0%)
• <state (pathway, brick)> == <state (brick pathway, upper left half)> (80.0%)

Q: What is the color of the pathway?
A: The color of the pathway is gray.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'pathway' in entity:                                             
  3             return scene_graph.get_attributes(entity).get('color', '')      
  4     return None                                                             
  5                                                                             

gpt-4o: The pathway is composed of rectangular bricks that are gray in color.
hscore: 78.46%
• <color (pathway, gray)> == <color (pathway's bricks, gray)"> (70.0%)
tscore: 83.83%
• <whole (pathway)> == <whole (pathway)> (100.0%)
• <part (pathway's bricks)> == <whole (brick pathway)> (80.0%)
• <color (pathway's bricks, gray)"> == <color (pathway, gray)> (70.0%)

Q: What’s written on the metal object?
A: The metal object, which is the manhole cover, has "A / W W" debossed on it.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'manhole cover' in entity:                                       
  3             return scene_graph.get_attributes(entity).get('text rendering', 
    '')                                                                         
  4     return None                                                             
  5                                                                             

gpt-4o: The metal object has the letters "W A" written on it.
hscore: 51.33%
• <text rendering (manhole cover, \A / W W\)> == <text rendering (metal object, \"W A\")"> (60.0%)
• <whole (manhole cover)> == <whole (metal object)> (50.0%)
• <state (text, debossed)> == <text rendering (metal object, \"W A\")"> (40.0%)
tscore: 75%
• <text rendering (metal object, \"W A\")"> == <image> (70.0%)
• <whole (metal object)> == <image> (70.0%)
Image
Caption

A top down view of a brown Labradoodle puppy standing to two hind legs leaning on a white wall. The puppy is trying to look over the edge of the wall. The floor is covered in a light blue wool rug. A blue stuffed animal and a purple strand of rope is to the right of the brown puppy. A black Labradoodle puppy with white paws is visible on the upper edge of the frame. Only the black puppy’s paws and nose are within the frame.

Scene Graph
    Scene Graph
QA + verification programs
Q: Where is the purple rope located in relation to the brown puppy?
A: The purple rope is to the right of the brown puppy.
   0 def execute_command(scene_graph):                                          
   1     for entity in scene_graph.get_entities():                              
   2         if 'rope' in entity:                                               
   3             attributes = scene_graph.get_attributes(entity)                
   4             if 'purple' in attributes.get('color', ''):                    
   5                 outgoing_relations =                                       
     scene_graph.get_outgoing_relations(entity)                                 
   6                 for target, relation in outgoing_relations.items():        
   7                     if 'puppy' in target and 'to the right of' in          
     relation.get('spatial', ''):                                               
   8                         return relation.get('spatial', '')                 
   9     return None                                                            
  10                                                                            

gpt-4o: The purple rope is located to the right of the brown puppy in the image.
hscore: 100%
• <spatial (rope, puppy, to the right of)> == <spatial (rope, puppy, to the right of)> (100.0%)
tscore: 98.85%
• <whole (rope)> == <whole (rope)> (100.0%)
• <color (rope, purple)> == <color (rope, purple)> (100.0%)
• <spatial (rope, puppy, to the right of)> == <spatial (rope, puppy, to the right of)> (100.0%)

Q: Describe the blue object in the scene.
A: The blue object in the scene is a stuffed animal.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'stuffed animal' in entity:                                      
  3             attributes = scene_graph.get_attributes(entity)                 
  4             if 'blue' in attributes.get('color', ''):                       
  5                 return                                                      
    scene_graph.describe(scene_graph.generate_subgraph([entity]))               
  6     return None                                                             
  7                                                                             

gpt-4o: The blue object in the scene appears to be a plush toy. It is located to the right of the puppy and has a soft, fabric texture. The toy is predominantly blue with some red elements, possibly indicating additional features or parts of the toy.
hscore: 82.59%
• <whole (blue object, stuffed animal)> == <whole (plush toy)> (80.0%)
tscore: 82.54%
• <whole (puppy)> == <whole (puppy)> (100.0%)
• <whole (plush toy)> == <whole (stuffed animal)> (90.0%)
• <color (plush toy, blue)> == <color (stuffed animal, blue)> (90.0%)
Image
Caption

A front view of a sculpture of a man standing up on a pile of gray cement blocks on a sidewalk. He is looking to the right and has a pair of shoes in the right hand and a golf bag in the left with some clubs in it. He has a short-sleeve collared shirt on and slacks. The sun is hitting the right side of his forehead. A stone wall to a building is behind him. On the left are a tree, plants, and dried twigs and leaves on the ground. A parking lot is visible in the distance on the left, as is a building. Part of a white parked car is visible. On the right, on the cement, part of a gray sculpture is visible on a black platform.

Scene Graph
    Scene Graph
QA + verification programs
Q: What is partially visible among the objects on the cement on the right side?
A: Part of a gray sculpture is visible on a black platform on the right.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if "sculpture" in entity:                                           
  3             relations = scene_graph.get_outgoing_relations(entity)          
  4             for target_entity, relation_info in relations.items():          
  5                 if "platform" in target_entity and "on" in                  
    relation_info.get('spatial', ''):                                           
  6                     return                                                  
    scene_graph.describe(scene_graph.generate_subgraph([entity]))               
  7     return None                                                             
  8                                                                             

gpt-4o: Partially visible among the objects on the cement on the right side is a black sculpture or statue. The visible portion appears to have a curved, textured surface with a pattern that resembles feathers or scales.
hscore: 55.74%
• <whole (sculpture)> == <whole (sculpture/statue)> (90.0%)
• <color (sculpture, gray)> == <material (sculpture/statue, black)> (60.0%)
• <spatial (sculpture, platform, on)> == <part (sculpture/statue's surface)> (50.0%)
tscore: 76.14%
• <whole (sculpture/statue)> == <whole (sculpture)> (90.0%)
• <state (sculpture/statue, right side)> == <state (sculpture, front view)> (80.0%)
• <state (sculpture/statue, partially visible)> == <state (sculpture, front view)> (80.0%)
Image
Caption

An outdoor long shot view looking down a long railroad track that is straight, and curves slightly to the left. The railroad track is placed on top of a ground floor made up of white rocks. About twenty-five feet to the left of the railroad track are two gray electrical boxes that are placed side by side, parallel to the railroad track, with about seven feet between them. Behind the electrical boxes is a field made up of dry yellow grass. To the right of the railroad track is a large maroon colored building, and two more multi-colored buildings behind it. Further behind the buildings, and hovering above them, is a large rectangular billboard that is colored blue, and has white letters on it that read "Feeling Stuck?". Further in the distance, to the left and right of the railroad track is a tree line consisting of tall bushy green trees. The sky is partly cloudy, and is a light baby blue color.

Scene Graph
    Scene Graph
QA + verification programs
Q: What color is the billboard hovering above the buildings?
A: The billboard hovering above the buildings is blue.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'billboard' in entity:                                           
  3             attributes = scene_graph.get_attributes(entity)                 
  4             if 'above' in                                                   
    scene_graph.get_outgoing_relations(entity).get('buildings',                 
    {}).get('spatial', ''):                                                     
  5                 return attributes.get('color', '')                          
  6     return None                                                             
  7                                                                             

gpt-4o: The billboard hovering above the buildings is primarily blue with some orange and white text.
hscore: 79.57%
• <color (billboard, blue)> == <color (billboard's background, blue)> (90.0%)
• <spatial (billboard, buildings, above)> == <state (billboard's text, above buildings)"> (60.0%)
tscore: 79.76%
• <whole (billboard)> == <whole (billboard)> (100.0%)
• <color (billboard's background, blue)> == <color (billboard, blue)> (90.0%)
• <whole (billboard's background)> == <whole (billboard)> (80.0%)

Q: How many electrical boxes are there and where are they located?
A: There are two gray electrical boxes parallel to the railroad track, with about seven feet between them and located about twenty-five feet to the left of the rail track.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'electrical boxes' in entity:                                    
  3             description =                                                   
    scene_graph.describe(scene_graph.generate_subgraph([entity]))               
  4             return description                                              
  5     return None                                                             
  6                                                                             

gpt-4o: There are two electrical boxes in the image. They are located to the left side of the railroad tracks, near the edge of the gravel area.
hscore: 73.88%
• <count (electrical boxes, ==2)> == <count (electrical boxes, ==2)> (100.0%)
• <spatial (electrical boxes, railroad track, to the left of)> == <spatial (electrical boxes, railroad tracks, to the left of)> (90.0%)
• <spatial (electrical boxes, railroad track, parallel to)> == <spatial (electrical boxes, railroad tracks, to the left of)> (80.0%)
tscore: 93.87%
• <whole (electrical boxes)> == <whole (electrical boxes)> (100.0%)
• <count (electrical boxes, ==2)> == <count (electrical boxes, ==2)> (100.0%)
• <spatial (electrical boxes, railroad tracks, to the left of)> == <spatial (electrical boxes, railroad track, to the left of)> (90.0%)

Q: What message is displayed on the billboard?
A: The message displayed on the billboard is "Feeling Stuck?"
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'billboard\'s letters' in entity:                                
  3             return scene_graph.get_attributes(entity).get('text rendering', 
    '').strip('"')                                                              
  4     return None                                                             
  5                                                                             

gpt-4o: The billboard displays the message: "Feeling Stuck? FREE College. No Debt."
hscore: 81.08%
• <text rendering (billboard, \Feeling Stuck?\)> == <text rendering (billboard, \"Feeling Stuck? FREE College. No Debt.\")> (80.0%)
tscore: 81.57%
• <whole (billboard)> == <whole (billboard)> (100.0%)
• <text rendering (billboard, \"Feeling Stuck? FREE College. No Debt.\")> == <text rendering (billboard's letters, "Feeling Stuck?")> (80.0%)
• <state (text, display on billboard)"> == <text rendering (billboard's letters, "Feeling Stuck?")> (60.0%)

Q: Can you describe the buildings in this scene?
A: There are three buildings: a large maroon-colored building to the right of the railroad track, and two multi-colored buildings behind it.
  0 def execute_command(scene_graph):                                           
  1     results = []                                                            
  2     for entity in scene_graph.get_entities():                               
  3         if 'building' in entity:                                            
  4             results.append(scene_graph.describe(scene_graph.generate_subgrap
    h([entity])))                                                               
  5     return ' '.join(results)                                                
  6                                                                             

gpt-4o: In the scene, there are a few buildings visible along the right side of the railroad tracks: 1. **Foreground Building**: This building is a single-story structure with a reddish-brown exterior. It has a few windows and appears to be a commercial or industrial building. There is some signage on the building, but the text is not fully legible. 2. **Background Buildings**: Further down the tracks, there are additional buildings that appear to be similar in style and function to the foreground building. They are also single-story structures with various colors and signage. 3. **Billboard**: Above the buildings, there is a large billboard with a blue background and white text. The billboard advertises a service related to education or career assistance. 4. **Utility Structures**: On the left side of the tracks, there are a couple of utility structures, possibly electrical or telecommunications boxes. They are white and have some text on them, indicating their purpose. The scene is set along a railroad track with gravel and a concrete crossing in the foreground. The area around the tracks is relatively open, with some grassy patches and a few trees in the distance.
hscore: 70.43%
• <whole (buildings)> == <whole (buildings)> (100.0%)
• <count (buildings, ==3)> == <count (buildings, > 2)> (90.0%)
• <whole (large building)> == <whole (buildings)> (80.0%)
tscore: 74.53%
• <whole (buildings)> == <whole (buildings)> (100.0%)
• <whole (trees)> == <whole (trees)> (100.0%)
• <color (billboard, blue)> == <color (billboard, blue)> (100.0%)

Q: What lies behind the electrical boxes?
A: Behind the electrical boxes is a field made up of dry yellow grass.
  0 def execute_command(scene_graph):                                           
  1     for entity in scene_graph.get_entities():                               
  2         if 'field' in entity:                                               
  3             if 'electrical boxes' in                                        
    scene_graph.get_outgoing_relations(entity):                                 
  4                 return                                                      
    scene_graph.describe(scene_graph.generate_subgraph([entity]))               
  5     return None                                                             
  6                                                                             

gpt-4o: Behind the electrical boxes in the image, there appears to be a grassy area with some trees and a few buildings in the distance. The area seems to be relatively open and not heavily developed. There are also some vehicles visible further back, indicating a road or parking area nearby.
hscore: 48.25%
• <state (field, dry)> == <state (grassy area, open)> (60.0%)
• <spatial (field, electrical boxes, behind)> == <spatial (grassy area, behind electrical boxes)> (50.0%)
• <whole (field)> == <whole (grassy area)> (50.0%)
tscore: 68.9%
• <spatial (vehicles, grassy area, further back)> == <image> (70.0%)
• <part (image, electrical boxes)> == <whole (electrical boxes)> (70.0%)
• <state (grassy area, not heavily developed)> == <image> (70.0%)