Triple
T8074748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orange Car Crash (Five Times) |
E188462
|
entity |
| Predicate | visualStructure |
P29429
|
FINISHED |
| Object | grid-like repetition |
—
|
LITERAL FINISHED |
How this triple was built (2 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: grid-like repetition | Statement: [Orange Car Crash (Five Times), visualStructure, grid-like repetition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualStructure Context triple: [Orange Car Crash (Five Times), visualStructure, grid-like repetition]
-
A.
displayStructure
Indicates that one entity presents or reveals the internal organization, layout, or arrangement of another entity.
-
B.
verticalStructure
Indicates a relationship where one entity is a structure that extends predominantly in the vertical direction relative to another reference or context.
-
C.
viaStructure
Indicates that one entity is connected to or accessed through a particular structural element or medium.
-
D.
visualElements
chosen
Indicates that one entity contains, uses, or is characterized by specific visual components or graphical features associated with another entity.
-
E.
visualSimplicity
Indicates that something is characterized by a minimal, uncluttered, and easy-to-perceive visual appearance or design.
- F. None of above.
Provenance (3 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_69ca82b50c708190863f661d438e68df |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb404c513c8190af54d6d6b6d1a81d |
completed | March 31, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69cb049f1614819087360d1a4c6f0faa |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:27 p.m.