Triple
T25430867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FUN |
E637248
|
entity |
| Predicate | airportHasLimitedTraffic |
P161647
|
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: [FUN, airportHasLimitedTraffic, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportHasLimitedTraffic Context triple: [FUN, airportHasLimitedTraffic, yes]
-
A.
hasAirportAccessTo
Indicates that one location or entity has direct access to another via an airport connection or service.
-
B.
hasMinorAirport
Indicates that a location or region is served by at least one smaller, secondary, or non-major airport.
-
C.
airportUse
Indicates that an airport is used or utilized by a particular entity, such as an airline, organization, or service.
-
D.
airportLocatedWithin
Indicates that an airport is geographically situated inside the boundaries of a specified area or region.
-
E.
airportServesMilitaryTraffic
Indicates that the airport accommodates or handles military air traffic in addition to any other types of traffic.
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6200ac60481909895c61d050b1338 |
completed | May 2, 2026, 4:02 p.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61f109ef48190873bfe18638d2046 |
completed | May 2, 2026, 3:58 p.m. |
Created at: April 21, 2026, 1:58 p.m.