Triple
T28193763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seoul–Busan |
E716382
|
entity |
| Predicate | approximateExpresswayDistanceKm |
P78936
|
FINISHED |
| Object | about 400 |
—
|
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 400 | Statement: [Seoul–Busan, approximateExpresswayDistanceKm, about 400]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateExpresswayDistanceKm Context triple: [Seoul–Busan, approximateExpresswayDistanceKm, about 400]
-
A.
approximateDistanceFromHighway1
Indicates the estimated distance between a location and Highway 1, rather than an exact measured value.
-
B.
approximateRouteLength
chosen
Indicates the estimated total distance or length of a given route, rather than its exact measured value.
-
C.
rangeHighwayApprox
Indicates that one entity is approximately within the range or vicinity of a highway associated with another entity.
-
D.
approximateDistanceKm
Indicates the estimated distance between two entities measured in kilometers, typically with some degree of inaccuracy or approximation.
-
E.
depthApproxKm
Indicates the approximate depth of something measured in kilometers.
- F. None of above.
Provenance (3 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_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
Created at: April 27, 2026, 10:26 p.m.