Triple
T650166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RAFAT |
E11327
|
entity |
| Predicate | liveryFeature |
P17744
|
FINISHED |
| Object | red-painted aircraft |
—
|
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: red-painted aircraft | Statement: [RAFAT, liveryFeature, red-painted aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: liveryFeature Context triple: [RAFAT, liveryFeature, red-painted aircraft]
-
A.
emblemFeatures
Indicates that an emblem includes or displays specific visual elements or characteristics.
-
B.
plumageFeature
Indicates a relationship where a specific characteristic or attribute is associated with an entity’s plumage (feathers).
-
C.
brandAttribute
Indicates that a specific attribute or characteristic is associated with, or describes, a particular brand.
-
D.
brandingFeature
Indicates that one entity serves as a branding-related characteristic, element, or attribute that helps define or distinguish another entity’s brand identity.
-
E.
colorOfTrailMarkings
Indicates the relationship specifying what color the trail’s markings are.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f31e70c81909a2ac1d939f7ec07 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0eade081909c47e85ed55f808d |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49df0de3c81909721eb391ec94031 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.