Triple
T2572328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UP Express at Union Station |
E57691
|
entity |
| Predicate | travelTimeToAirport |
P39869
|
FINISHED |
| Object | approximately 25 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: approximately 25 minutes | Statement: [UP Express at Union Station, travelTimeToAirport, approximately 25 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeToAirport Context triple: [UP Express at Union Station, travelTimeToAirport, approximately 25 minutes]
-
A.
approximateTravelTimeToSheremetyevo
Indicates the estimated amount of time it typically takes to travel from a given location to Sheremetyevo.
-
B.
approximateTravelTimeToVnukovo
Indicates the estimated duration it typically takes to travel from a given location to Vnukovo.
-
C.
flightDuration
Indicates the length of time that a specific flight takes from departure to arrival.
-
D.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
-
E.
approximateTravelTimeToDomodedovo
Indicates the estimated amount of time it typically takes to travel from a given location to Domodedovo.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3853c848190970e8a2da16d726d |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd251b48c8190862c7b39ea1bf8ea |
completed | March 7, 2026, 7:22 a.m. |
Created at: March 6, 2026, 9:48 p.m.