Triple
T25430859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FUN |
E637248
|
entity |
| Predicate | airportHasTerminal |
P34629
|
FINISHED |
| Object | single terminal building |
—
|
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: single terminal building | Statement: [FUN, airportHasTerminal, single terminal building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportHasTerminal Context triple: [FUN, airportHasTerminal, single terminal building]
-
A.
airportHasTerminals
chosen
Indicates that a particular airport includes or is composed of one or more terminal facilities.
-
B.
hasNumberOfPassengerTerminalsAtAirport
Indicates the relationship that specifies how many passenger terminals are present at a given airport.
-
C.
airportTypePresent
Indicates that a specific type or category of airport is present or exists in relation to the referenced entity.
-
D.
hasStationAtAirport
Indicates that an organization or service operates a station or facility located at a specific airport.
-
E.
hasPassengerTerminalSector
Indicates that a passenger terminal is divided into or associated with a specific sector or subsection within it.
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f6d9e4b081908aa8d80bb6ea2b02 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f49377411c8190b2188de444d76795 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 21, 2026, 1:58 p.m.