Triple
T28052582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | REDWOOD |
E708866
|
entity |
| Predicate | airlineOperationalBase |
P31126
|
FINISHED |
| Object | San Francisco International Airport |
—
|
NE NERFINISHED |
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: San Francisco International Airport | Statement: [REDWOOD, airlineOperationalBase, San Francisco International Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineOperationalBase Context triple: [REDWOOD, airlineOperationalBase, San Francisco International Airport]
-
A.
operatingBaseAirport
chosen
Indicates the airport that serves as the primary base of operations for an airline or aircraft.
-
B.
airlineBaseCity
Indicates the city that serves as the primary operational base or headquarters location for an airline.
-
C.
servesAsPrimaryAirportOperatorForCity
Indicates that an entity functions as the main organization responsible for operating the primary airport serving a particular city.
-
D.
associatedAirlineHeadquarters
Indicates that an airline is connected to or based at a particular headquarters location.
-
E.
airlineHub
Indicates that a particular location (typically an airport or city) serves as a central hub or primary operational base for an airline.
- 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_69ef9b6df9f48190bbb971d02cbe1b65 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f64dbbaefc8190952b8320bf4397d8 |
completed | May 2, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 8:34 p.m.