Triple
T1825025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aeroexpress train |
E40632
|
entity |
| Predicate | approximateTravelTimeToDomodedovo |
P34228
|
FINISHED |
| Object | about 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 45 minutes | Statement: [Aeroexpress train, approximateTravelTimeToDomodedovo, about 45 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateTravelTimeToDomodedovo Context triple: [Aeroexpress train, approximateTravelTimeToDomodedovo, about 45 minutes]
-
A.
distanceFromMoscow_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
-
B.
otherMoscowAirport
Indicates that one airport is another airport located in Moscow, distinguishing between multiple Moscow-area airports.
-
C.
flightDuration
Indicates the length of time that a specific flight takes from departure to arrival.
-
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.