Triple
T10730467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chungbuk Line |
E253057
|
entity |
| Predicate | connectsToRailwayNetwork |
P95666
|
FINISHED |
| Object | national rail network of South Korea |
—
|
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: national rail network of South Korea | Statement: [Chungbuk Line, connectsToRailwayNetwork, national rail network of South Korea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsToRailwayNetwork Context triple: [Chungbuk Line, connectsToRailwayNetwork, national rail network of South Korea]
-
A.
usesRailInfrastructureOf
Indicates that one entity operates on, accesses, or otherwise makes use of the rail infrastructure owned or managed by another entity.
-
B.
connectsToRailStation
Indicates that one entity has a direct link, route, or access connection to a rail station.
-
C.
hasPassengerRailConnection
Indicates that there exists a passenger rail service linking one location or transport node to another.
-
D.
hasRailwayInfrastructureType
Indicates that an entity possesses or is associated with a specific type or category of railway infrastructure.
-
E.
hasRackRailway
Indicates that one entity possesses or includes a rack railway system connecting locations or operating within its area.
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d70fcb1cd881909635def59ad5d19c |
completed | April 9, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69d6f309a44881908e49e3ba478c35b4 |
completed | April 9, 2026, 12:30 a.m. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:14 p.m.