Triple
T1825026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aeroexpress train |
E40632
|
entity |
| Predicate | approximateTravelTimeToSheremetyevo |
P34229
|
FINISHED |
| Object | about 35–45 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 35–45 minutes | Statement: [Aeroexpress train, approximateTravelTimeToSheremetyevo, about 35–45 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateTravelTimeToSheremetyevo Context triple: [Aeroexpress train, approximateTravelTimeToSheremetyevo, about 35–45 minutes]
-
A.
otherMoscowAirport
Indicates that one airport is another airport located in Moscow, distinguishing between multiple Moscow-area airports.
-
B.
flightDuration
Indicates the length of time that a specific flight takes from departure to arrival.
-
C.
passengersCountApproximate
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
-
D.
otherMajorMoscowAirports
Indicates that the referenced airports are major airports serving Moscow other than the primary one under consideration.
-
E.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
- 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_69a8864644bc8190b2358ab897194ac1 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb45402688190b9a535b14030c354 |
completed | March 7, 2026, 5:15 a.m. |
| PD | Predicate disambiguation | batch_69abafd6a9948190ac2b2743db6f8f69 |
completed | March 7, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69abb4517f9c8190a5d9bc965a4f29c9 |
completed | March 7, 2026, 5:14 a.m. |
Created at: March 4, 2026, 7:32 p.m.