Triple
T12954170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MTR Airport Express |
E309967
|
entity |
| Predicate | travelTimeHongKongToAirport |
P39869
|
FINISHED |
| Object | about 24 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 24 minutes | Statement: [MTR Airport Express, travelTimeHongKongToAirport, about 24 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeHongKongToAirport Context triple: [MTR Airport Express, travelTimeHongKongToAirport, about 24 minutes]
-
A.
travelTimeToAirport
chosen
Indicates the amount of time required to travel from a given location to an airport.
-
B.
approximateTravelTimeAirportToOsloS_minutes
Indicates the estimated duration, in minutes, required to travel from an airport to Oslo.
-
C.
approximateTravelTimeToVnukovo
Indicates the estimated duration it typically takes to travel from a given location to Vnukovo.
-
D.
distanceToAirport
Indicates the measured distance between a given location and the nearest or specified airport.
-
E.
approximateTravelTimeToSheremetyevo
Indicates the estimated amount of time it typically takes to travel from a given location to Sheremetyevo.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:44 p.m.