Triple
T22972872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Austria |
E571234
|
entity |
| Predicate | aspectRatioRange |
P1991
|
FINISHED |
| Object | between 2:3 and 3:5 in some uses |
—
|
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: between 2:3 and 3:5 in some uses | Statement: [Flag of Austria, aspectRatioRange, between 2:3 and 3:5 in some uses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aspectRatioRange Context triple: [Flag of Austria, aspectRatioRange, between 2:3 and 3:5 in some uses]
-
A.
aspectRatio
chosen
Indicates the proportional relationship between an entity’s width and its height.
-
B.
aspectRatioWidth
Indicates the proportional width component in an aspect ratio relationship between dimensions.
-
C.
spatialAspect
Indicates how something is positioned, oriented, or arranged in space relative to other entities or a reference frame.
-
D.
mediaAspect
Indicates the specific aspect ratio or dimensional proportion of a media item in relation to its width and height.
-
E.
typicalAspect
Indicates that something represents a characteristic or commonly occurring aspect of another thing or situation.
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182343a448190a5259cdf721c9d04 |
completed | April 29, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:48 p.m.