Triple
T8407883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spirit of St. Louis Airport |
E198544
|
entity |
| Predicate | hasCorporateFlightDepartments |
P81834
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Spirit of St. Louis Airport, hasCorporateFlightDepartments, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCorporateFlightDepartments Context triple: [Spirit of St. Louis Airport, hasCorporateFlightDepartments, yes]
-
A.
hasAirlines
Indicates that one entity (such as an airport, city, or country) is served by or associated with one or more airline operators.
-
B.
ownsAirline
Indicates that one entity has legal ownership or controlling interest in an airline company.
-
C.
hasScheduledFlights
Indicates that there are one or more flights planned and set to occur between the related entities according to a schedule.
-
D.
associatedAirlineHeadquarters
Indicates that an airline is connected to or based at a particular headquarters location.
-
E.
hasCorporateOffice
Indicates that an entity maintains a formal corporate office at a specified location or within another organizational entity.
- 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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb8315a8a8819097f6da11b909b527 |
completed | March 31, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69cb70d473dc8190af8ea81ee5aa970d |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76da264881909483b835e1db06da |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 6:05 p.m.