Triple
T382823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Bourget Field |
E8716
|
entity |
| Predicate | ceasedMajorInternationalPassengerTraffic |
P10700
|
FINISHED |
| Object | 1977 |
—
|
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: 1977 | Statement: [Le Bourget Field, ceasedMajorInternationalPassengerTraffic, 1977]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ceasedMajorInternationalPassengerTraffic Context triple: [Le Bourget Field, ceasedMajorInternationalPassengerTraffic, 1977]
-
A.
isMajorInternationalGatewayFor
Indicates that one entity serves as a primary, globally significant access point or hub for another entity’s international connections or flows.
-
B.
peakPassengerTrafficRank
Indicates the relative position of an entity in an ordered list based on the amount of passenger traffic it experiences at its peak.
-
C.
passengerTrafficRankUS
Indicates the relative ranking of a location or facility within the United States based on the volume of passenger traffic it handles.
-
D.
totalPeopleFlown
Indicates the total number of people who have been transported by a given flight, airline, or transportation operation.
-
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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec40ff8c81909306eb2dfe1512af |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96602188190b0cbc167f55a9237 |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ea2dc3088190a2aeb4496aff3582 |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.