Triple
T9354239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pyeongtaek–Jecheon Expressway |
E225093
|
entity |
| Predicate | roleInTransportNetwork |
P6821
|
FINISHED |
| Object | major east–west corridor |
—
|
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: major east–west corridor | Statement: [Pyeongtaek–Jecheon Expressway, roleInTransportNetwork, major east–west corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInTransportNetwork Context triple: [Pyeongtaek–Jecheon Expressway, roleInTransportNetwork, major east–west corridor]
-
A.
transportationRole
chosen
Indicates a role or function that an entity has specifically in the context of providing, operating, or supporting transportation.
-
B.
mobilityRole
Indicates the functional role or capacity an entity has in enabling, supporting, or performing movement or transportation.
-
C.
hasPublicTransitRole
Indicates that an entity holds a specific functional role or responsibility within a public transit system.
-
D.
transportRole
Indicates that an entity participates in a transportation process with a specific functional role (e.g., carrier, passenger, cargo, or operator).
-
E.
roleInWhiteBuses
Indicates that an entity participated in or held a specific role within the White Buses operation.
- 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f96c9a8819091bf63909bdcdf91 |
completed | April 1, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69cc7a68ab9481909f97cb70764697cc |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:42 p.m.