Triple
T3616882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badhoevedorp |
E76622
|
entity |
| Predicate | hasAirportRelatedFunction |
P50462
|
FINISHED |
| Object | airport village |
—
|
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: airport village | Statement: [Badhoevedorp, hasAirportRelatedFunction, airport village]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAirportRelatedFunction Context triple: [Badhoevedorp, hasAirportRelatedFunction, airport village]
-
A.
hasStationAtAirport
Indicates that an organization or service operates a station or facility located at a specific airport.
-
B.
hasEndpointAirport
Indicates that something, such as a route or flight, has a specific airport as one of its terminal endpoints.
-
C.
hasAirportWithinJurisdiction
Indicates that a governing authority or administrative region has legal or administrative control over an airport located within its boundaries.
-
D.
belongsToAirport
Indicates that one entity is part of, associated with, or under the jurisdiction of a specific airport.
-
E.
airportServesAs
Indicates that an airport functions in a particular role or capacity (such as primary, secondary, or hub) for a specified area, organization, or service.
- 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_69ad85dae2fc81908d1ceadbc6af0089 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc27c98088190a493c9eddf6b206a |
completed | March 8, 2026, 6:39 p.m. |
| PD | Predicate disambiguation | batch_69adb83f1e4c8190ab501c1c05b14c08 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb9bbb62c8190989629ca11733e1b |
completed | March 8, 2026, 6:02 p.m. |
Created at: March 8, 2026, 3:23 p.m.