Triple
T21658246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hwang River |
E534524
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Goryeong County |
—
|
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: Goryeong County | Statement: [Hwang River, flowsThrough, Goryeong County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goryeong County Context triple: [Hwang River, flowsThrough, Goryeong County]
-
A.
Goryeong County
chosen
Goryeong County is a rural administrative region in southeastern South Korea known for its historical sites and agricultural landscape.
-
B.
Eumseong County
Eumseong County is a rural administrative region in North Chungcheong Province, South Korea, known as the birthplace of former UN Secretary-General Ban Ki-moon.
-
C.
Yeongdeok County
Yeongdeok County is a coastal county in eastern South Korea known for its scenic shoreline and seafood, particularly snow crabs.
-
D.
Yeoncheon County
Yeoncheon County is a rural county in Gyeonggi Province, South Korea, known for its location near the Demilitarized Zone (DMZ) and its historical military significance.
-
E.
Seongju County
Seongju County is a rural administrative region in southeastern South Korea known for its melon farming and traditional cultural heritage.
- 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c05a8d881909f747635bdb4ef09 |
completed | April 27, 2026, 2 p.m. |
Created at: April 16, 2026, 6:36 p.m.