Triple
T10602348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stuart K. Card |
E275781
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Readings in Information Visualization: Using Vision to Think
Readings in Information Visualization: Using Vision to Think is an influential anthology that compiles foundational research and key perspectives on how visual representations support human thinking and data analysis in the field of information visualization.
|
E874566
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Readings in Information Visualization: Using Vision to Think | Statement: [Stuart K. Card, notableWork, Readings in Information Visualization: Using Vision to Think]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Readings in Information Visualization: Using Vision to Think Context triple: [Stuart K. Card, notableWork, Readings in Information Visualization: Using Vision to Think]
-
A.
On Vision and Colors
On Vision and Colors is Arthur Schopenhauer’s early philosophical treatise that expands and critiques Goethe’s color theory by offering a metaphysical and physiological account of human color perception.
-
B.
The Psychology of Computer Vision (edited volume)
The Psychology of Computer Vision is an influential edited volume, compiled by Patrick Henry Winston, that brings together foundational research exploring how principles of human perception and cognition can inform and advance computer vision.
-
C.
Onyx visualization systems
Onyx visualization systems are high-performance graphics supercomputers from SGI designed for advanced 3D visualization, simulation, and scientific computing applications.
-
D.
ImageWorks: The What-If Labs
ImageWorks: The What-If Labs is an interactive, hands-on exhibit at Epcot where guests can explore creativity and sensory illusions through playful, imaginative experiments.
-
E.
Learning from Las Vegas
Learning from Las Vegas is an influential architectural theory book by Robert Venturi, Denise Scott Brown, and Steven Izenour that helped define postmodern architecture by championing the symbolism and vernacular of commercial landscapes like the Las Vegas Strip.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Readings in Information Visualization: Using Vision to Think Triple: [Stuart K. Card, notableWork, Readings in Information Visualization: Using Vision to Think]
Generated description
Readings in Information Visualization: Using Vision to Think is an influential anthology that compiles foundational research and key perspectives on how visual representations support human thinking and data analysis in the field of information visualization.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Readings in Information Visualization: Using Vision to Think Target entity description: Readings in Information Visualization: Using Vision to Think is an influential anthology that compiles foundational research and key perspectives on how visual representations support human thinking and data analysis in the field of information visualization.
-
A.
On Vision and Colors
On Vision and Colors is Arthur Schopenhauer’s early philosophical treatise that expands and critiques Goethe’s color theory by offering a metaphysical and physiological account of human color perception.
-
B.
The Psychology of Computer Vision (edited volume)
The Psychology of Computer Vision is an influential edited volume, compiled by Patrick Henry Winston, that brings together foundational research exploring how principles of human perception and cognition can inform and advance computer vision.
-
C.
Onyx visualization systems
Onyx visualization systems are high-performance graphics supercomputers from SGI designed for advanced 3D visualization, simulation, and scientific computing applications.
-
D.
ImageWorks: The What-If Labs
ImageWorks: The What-If Labs is an interactive, hands-on exhibit at Epcot where guests can explore creativity and sensory illusions through playful, imaginative experiments.
-
E.
Learning from Las Vegas
Learning from Las Vegas is an influential architectural theory book by Robert Venturi, Denise Scott Brown, and Steven Izenour that helped define postmodern architecture by championing the symbolism and vernacular of commercial landscapes like the Las Vegas Strip.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6ded61d5c8190b13890c964b59949 |
completed | April 8, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95eaffcd0819098e0a06a731b602f |
completed | April 10, 2026, 8:33 p.m. |
| NEDg | Description generation | batch_69d961aaf71881908289244e0a490492 |
completed | April 10, 2026, 8:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d9623cf54081908abcdc88e13d5176 |
completed | April 10, 2026, 8:49 p.m. |
Created at: April 8, 2026, 7:31 p.m.