Triple
T6810231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daejeon Metro |
E156610
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object | Daejeon Metro Line 1 |
E156610
|
NE 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: Daejeon Metro Line 1 | Statement: [Daejeon Metro, hasLine, Daejeon Metro Line 1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daejeon Metro Line 1 Context triple: [Daejeon Metro, hasLine, Daejeon Metro Line 1]
-
A.
Daejeon Metro
chosen
Daejeon Metro is the urban rapid transit system serving the city of Daejeon in South Korea.
-
B.
Gwangju Metro
Gwangju Metro is the urban rapid transit system serving the city of Gwangju in South Korea.
-
C.
Shinbundang Line
The Shinbundang Line is a high-speed, driverless subway line in the Seoul metropolitan area that connects southern Seoul with the satellite city of Bundang.
-
D.
Suin–Bundang Line
The Suin–Bundang Line is a major commuter rail line in the Seoul metropolitan area that connects southeastern Seoul with surrounding cities such as Seongnam, Yongin, and Suwon.
-
E.
Daegu Metro
Daegu Metro is the urban rapid transit system serving the city of Daegu in South Korea, providing high-capacity rail transportation across the metropolitan area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d30ded6481908fd64611607c610e |
completed | March 27, 2026, 6:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a309dd4c81909f2a652f211911bc |
completed | March 28, 2026, 9:44 a.m. |
Created at: March 27, 2026, 2:16 p.m.