Triple
T26734891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sapsan high-speed trains |
E674082
|
entity |
| Predicate | travelTimeMoscowSaintPetersburg |
P163068
|
FINISHED |
| Object | about 3.5–4 hours |
—
|
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 3.5–4 hours | Statement: [Sapsan high-speed trains, travelTimeMoscowSaintPetersburg, about 3.5–4 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeMoscowSaintPetersburg Context triple: [Sapsan high-speed trains, travelTimeMoscowSaintPetersburg, about 3.5–4 hours]
-
A.
approximateTravelTimeToDomodedovo
Indicates the estimated amount of time it typically takes to travel from a given location to Domodedovo.
-
B.
distanceFromSaintPetersburg
Indicates the spatial distance between a given entity and the city of Saint Petersburg.
-
C.
distanceDirectionFromMoscow
Indicates the relative distance and compass direction of one location measured from Moscow.
-
D.
distanceFromMoscow_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
-
E.
approximateTravelTimeToVnukovo
Indicates the estimated duration it typically takes to travel from a given location to Vnukovo.
- 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_69eecda57ab481909424e98f2835e7d8 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f63639a84c81909d700a539b458b42 |
completed | May 2, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
| PDg | Predicate description generation | batch_69f6352df6148190bc10772cd40bd7b3 |
completed | May 2, 2026, 5:32 p.m. |
Created at: April 27, 2026, 3:46 a.m.