Triple
T19117232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 6 |
E467936
|
entity |
| Predicate | hasLoopSection |
P36766
|
FINISHED |
| Object | Eungam 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: Eungam Station | Statement: [Line 6, hasLoopSection, Eungam Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eungam Station Context triple: [Line 6, hasLoopSection, Eungam Station]
-
A.
Eungam Station
chosen
Eungam Station is a subway station in Seoul, South Korea, serving as a key stop on Seoul Subway Line 6.
-
B.
Bonghwasan Station
Bonghwasan Station is a subway station in Seoul, South Korea, serving as the northeastern terminus of Seoul Subway Line 6.
-
C.
Miryang Station
Miryang Station is a major railway station in Miryang, South Korea, serving as an important junction on the country’s rail network.
-
D.
Beomgye Station
Beomgye Station is a subway station in Anyang, South Korea, serving as a local transit hub on the Seoul metropolitan rail network.
-
E.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
- 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e399a6d8819090a9501ff1637b9d |
completed | April 20, 2026, 8:28 a.m. |
Created at: April 10, 2026, 12:05 p.m.