Triple
T14762594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seodaemun-gu |
E346906
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Sinchon Station |
E1112841
|
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: Sinchon Station | Statement: [Seodaemun-gu, contains, Sinchon Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sinchon Station Context triple: [Seodaemun-gu, contains, Sinchon Station]
-
A.
Sinchon Station
chosen
Sinchon Station is a major subway station in Seoul, South Korea, serving the bustling Sinchon area known for its universities, shopping, and nightlife.
-
B.
Kwangbok Station
Kwangbok Station is a stop on the Pyongyang Metro system in North Korea, serving passengers along one of the capital’s main underground transit lines.
-
C.
Pyeongchon Station
Pyeongchon Station is a subway station in Anyang, South Korea, serving as a key stop on Seoul Subway Line 4 and providing commuter access between Anyang and the greater Seoul metropolitan area.
-
D.
Myeongnyun Station
Myeongnyun Station is a metro station in Busan, South Korea, serving the Dongnae District on the Busan Metro network.
-
E.
Seodaejeon Station
Seodaejeon Station is a major railway station in Daejeon, South Korea, serving as an important stop on national rail lines including high-speed services.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f3a1608190b1b17624003a0c7f |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cf24c0081909221cb7d761e882f |
completed | May 8, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:30 a.m.