Triple
T18157025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monaco Heliport |
E434657
|
entity |
| Predicate | typicalFlightTimeToNiceAirport |
P1526
|
FINISHED |
| Object | about 7 minutes |
—
|
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: about 7 minutes | Statement: [Monaco Heliport, typicalFlightTimeToNiceAirport, about 7 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFlightTimeToNiceAirport Context triple: [Monaco Heliport, typicalFlightTimeToNiceAirport, about 7 minutes]
-
A.
distanceFromNice
Indicates the spatial distance between an entity and the location referred to as Nice.
-
B.
flightDuration
chosen
Indicates the length of time that a specific flight takes from departure to arrival.
-
C.
distanceFromNiceByRoad_km
Indicates the length of the road route, in kilometers, from the city of Nice to the given location.
-
D.
distanceToNiceKilometers
Indicates the physical distance, measured in kilometers, between an entity and the city of Nice.
-
E.
typicalTravelTimeParisAmsterdam
Indicates the usual or average amount of time it takes to travel between Paris and Amsterdam.
- F. None of above.
Provenance (3 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4debf43348190a22f23a4bbfab433 |
completed | April 19, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:30 a.m.