Triple
T382827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Bourget Field |
E8716
|
entity |
| Predicate | ParisAirShowFrequency |
P10701
|
FINISHED |
| Object | biennial |
—
|
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: biennial | Statement: [Le Bourget Field, ParisAirShowFrequency, biennial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ParisAirShowFrequency Context triple: [Le Bourget Field, ParisAirShowFrequency, biennial]
-
A.
airportRankInFranceByTraffic
Indicates the relative position of an airport in France when airports are ordered by the volume of passenger or cargo traffic they handle.
-
B.
airTraffic
Indicates the movement and flow of aircraft through airspace, including their routes, density, and interactions while in flight.
-
C.
otherMainParisAirport
Indicates that one airport serves as an alternative primary airport to another in the Paris area.
-
D.
frequencyBand
Indicates the specific range of frequencies within which a signal, measurement, or phenomenon is defined or operates.
-
E.
flightRules
Indicates the regulatory or procedural rules that govern how a flight must be conducted or operated.
- 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.