Triple
T559090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zurich |
E13407
|
entity |
| Predicate | airportServesAs |
P16381
|
FINISHED |
| Object | international hub |
—
|
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: international hub | Statement: [Zurich, airportServesAs, international hub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportServesAs Context triple: [Zurich, airportServesAs, international hub]
-
A.
airportServed
Indicates that a particular airport provides service to, or is used for air travel to and from, a given location or area.
-
B.
servesAirport
Indicates that a transportation service or route provides access to and operates for a particular airport.
-
C.
airportLocatedIn
Indicates that an airport is geographically situated within a specific administrative or territorial area.
-
D.
hasMajorAirport
Indicates that a location possesses at least one significant airport that serves as a primary hub for air travel in that area.
-
E.
hasInternationalAirport
Indicates that a place possesses an airport that handles international flights and services cross-border air 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499df43f08190b514a38d36fc271d |
completed | March 1, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69a494bd78e8819083c519669158f209 |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985952a481908b918350ececf484 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:32 p.m.