Triple
T8363606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KTX |
E197067
|
entity |
| Predicate | terminusStation |
P15150
|
FINISHED |
| Object | Seoul Station |
E467238
|
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: Seoul Station | Statement: [KTX, terminusStation, Seoul Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seoul Station Context triple: [KTX, terminusStation, Seoul Station]
-
A.
Seoul Station
chosen
Seoul Station is a major railway and transportation hub in central Seoul, South Korea, serving high-speed, intercity, and commuter trains as well as multiple subway lines.
-
B.
Yeonsan Station
Yeonsan Station is a major transit hub in Busan, South Korea, serving as an important interchange point on the city’s subway network.
-
C.
Daejeon Station
Daejeon Station is a major railway hub in central South Korea, serving high-speed KTX trains and connecting Daejeon to key cities nationwide.
-
D.
Daegu Station
Daegu Station is a major railway and metro hub in Daegu, South Korea, serving as a key transit point for regional and urban transportation.
-
E.
Yeouido Station
Yeouido Station is a major Seoul Metropolitan Subway station on Yeouido Island that serves as a key transit hub for the city’s financial and business district.
- 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_69ca82f2dbe48190aba982e75a0d94de |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80768b208190a5f6c9e6cb6e7f30 |
completed | March 31, 2026, 8:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde7c747b48190b1979b4eaf281df5 |
completed | April 2, 2026, 3:51 a.m. |
Created at: March 30, 2026, 6 p.m.