Triple
T28193765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seoul–Busan |
E716382
|
entity |
| Predicate | typicalExpressBusTravelTime |
P202319
|
FINISHED |
| Object | about 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 4 hours | Statement: [Seoul–Busan, typicalExpressBusTravelTime, about 4 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalExpressBusTravelTime Context triple: [Seoul–Busan, typicalExpressBusTravelTime, about 4 hours]
-
A.
travelTimeTypical
Indicates the usual or expected amount of time it takes to travel between two locations under normal conditions.
-
B.
bestTravelTime
Indicates the most optimal duration or period required to travel between specified locations under given conditions.
-
C.
hasApproximateFastRailJourneyTimeMinutes
Indicates that there is an estimated duration, measured in minutes, for a fast rail journey between two locations.
-
D.
travelTimeAdvantage
Indicates that one option provides a shorter or more favorable travel time compared to another.
-
E.
hasApproximateFastRailJourneyTimeHours
Indicates that there is an estimated duration, measured in hours, for a fast rail journey between the related entities.
- 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_69efd6b612f48190a72012b520afbd10 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_6a007241df8081909dbad651fda82aa7 |
completed | May 10, 2026, 11:55 a.m. |
| PD | Predicate disambiguation | batch_6a0071e77ed081908cd618da8977d878 |
completed | May 10, 2026, 11:54 a.m. |
| PDg | Predicate description generation | batch_6a007240adac819087ab65e9733c384f |
completed | May 10, 2026, 11:55 a.m. |
Created at: April 27, 2026, 10:26 p.m.