Triple
T22246075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Arizona |
E549843
|
entity |
| Predicate | aspectRatioWidth |
P147534
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Flag of Arizona, aspectRatioWidth, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aspectRatioWidth Context triple: [Flag of Arizona, aspectRatioWidth, 3]
-
A.
aspectRatio
Indicates the proportional relationship between an entity’s width and its height.
-
B.
sideRatioLength
Indicates the proportional relationship between the lengths of two or more sides in a geometric figure.
-
C.
typicalAspect
Indicates that something represents a characteristic or commonly occurring aspect of another thing or situation.
-
D.
mediaAspect
Indicates the specific aspect ratio or dimensional proportion of a media item in relation to its width and height.
-
E.
anamorphicSqueezeFactor
Indicates the degree to which an image or signal has been horizontally compressed (or must be expanded) by an anamorphic process, expressed as a scaling factor.
- F. None of above. chosen
Provenance (4 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_69e11e41d9408190bd770cf282e22753 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f13217c9f88190aa2ce7d644b57739 |
completed | April 28, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69e72fe1e0cc8190bd13cff2a0846225 |
completed | April 21, 2026, 8:05 a.m. |
| PDg | Predicate description generation | batch_69e7342ce08c8190bc0a7085f4a952e7 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 8:38 p.m.