Triple
T9048703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanilla Air |
E216825
|
entity |
| Predicate | airlineAllianceType |
P86073
|
FINISHED |
| Object | low-cost carrier alliance |
—
|
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: low-cost carrier alliance | Statement: [Vanilla Air, airlineAllianceType, low-cost carrier alliance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineAllianceType Context triple: [Vanilla Air, airlineAllianceType, low-cost carrier alliance]
-
A.
airlineAllianceMembership
Indicates that an airline is a member of a specific airline alliance.
-
B.
airlineAllianceContext
Indicates the contextual relationship between an airline and its membership or participation status within a specific airline alliance.
-
C.
airlineAllianceStatus
Indicates the formal alliance membership or partnership status that exists between an airline and an airline alliance.
-
D.
airlineAllianceRelationship
Indicates that two or more airlines are connected through a formal alliance or partnership arrangement.
-
E.
airlineAllianceScope
Indicates the extent or coverage of an airline alliance’s operations or cooperation (e.g., regional vs. global).
- 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_69ca83d362e88190ae44b4e4dc194209 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6b51aa708190a37feecfd8deed2f |
completed | April 1, 2026, 12:48 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee566b081909e3cdaf551dbd0ec |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5f4f1cb48190a025d1b3d8d7a790 |
completed | March 31, 2026, 11:57 p.m. |
Created at: March 30, 2026, 7:09 p.m.