Triple
T37901567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allegro train service |
E945426
|
entity |
| Predicate | travelTimeHelsinkiToStPetersburg |
P192338
|
FINISHED |
| Object | about 3.5 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 hours | Statement: [Allegro train service, travelTimeHelsinkiToStPetersburg, about 3.5 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeHelsinkiToStPetersburg Context triple: [Allegro train service, travelTimeHelsinkiToStPetersburg, about 3.5 hours]
-
A.
travelTimeMoscowSaintPetersburg
Indicates the duration of travel required to go from Moscow to Saint Petersburg.
-
B.
drivingTimeToHelsinkiApprox
Indicates an approximate amount of time it takes to drive from a given location to Helsinki.
-
C.
distanceFromSaintPetersburg
Indicates the spatial distance between a given entity and the city of Saint Petersburg.
-
D.
distanceToHelsinki_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Helsinki.
-
E.
distanceToPori
Indicates the measured distance from a given entity or location to Pori.
- 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_69f76ef20bb0819088b5b6ceecb0b8fc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd05ba6b2c81909c62b46237d10365 |
completed | May 7, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69fd03039e48819082b6e12c5453885a |
completed | May 7, 2026, 9:24 p.m. |
| PDg | Predicate description generation | batch_69fd05b965608190a3666410b9f8e125 |
completed | May 7, 2026, 9:35 p.m. |
Created at: May 3, 2026, 4:20 p.m.