Triple
T22630795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaeson Station |
E558542
|
entity |
| Predicate | adjacentStation |
P5707
|
FINISHED |
| Object | Tongil Station |
—
|
NE NERFINISHED |
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: Tongil Station | Statement: [Kaeson Station, adjacentStation, Tongil Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tongil Station Context triple: [Kaeson Station, adjacentStation, Tongil Station]
-
A.
Tongil Station
chosen
Tongil Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
B.
Sillim Station
Sillim Station is a major Seoul Metropolitan Subway station in southwestern Seoul, serving as a busy transit hub for commuters in the Gwanak-gu area.
-
C.
Nampo Station
Nampo Station is a major subway station and commercial hub in central Busan, South Korea, known for its proximity to popular shopping streets and tourist attractions.
-
D.
Jonu Station
Jonu Station is a stop on the Pyongyang Metro system in North Korea, serving passengers on one of the capital’s main urban rail lines.
-
E.
Magongnaru Station
Magongnaru Station is a railway station in Seoul, South Korea, serving the Airport Railroad Express (AREX) line and connecting the city to Incheon International Airport.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245467d9881908d6985bd0db7a1f1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17008e7648190b243c18067b4efb9 |
completed | April 29, 2026, 2:42 a.m. |
Created at: April 17, 2026, 3:02 p.m.