Triple
T6563827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulju-gun |
E153850
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Onyang-eup |
E606591
|
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: Onyang-eup | Statement: [Ulju-gun, hasSubdivision, Onyang-eup]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Onyang-eup Context triple: [Ulju-gun, hasSubdivision, Onyang-eup]
-
A.
Eonyang-eup
chosen
Eonyang-eup is a town in Ulju County, Ulsan, South Korea, known as a local administrative and commercial hub for the surrounding region.
-
B.
Geumwang-eup
Geumwang-eup is a town-level administrative division in Eumseong County, located in North Chungcheong Province, South Korea.
-
C.
Eumseong-eup
Eumseong-eup is the main urban township and administrative center of Eumseong County in North Chungcheong Province, South Korea.
-
D.
Samseong-myeon
Samseong-myeon is a rural township-level administrative area within Eumseong County in North Chungcheong Province, South Korea.
-
E.
Suyŏng-gu
Suyŏng-gu is an urban district of Busan, South Korea, known for its coastal location and role as a residential and commercial hub within the city.
- 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_69c6880cb35881909b763eb0125236b9 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae3a40488190892d20ca0d60b937 |
completed | March 27, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f7867e688190aad8cc2b396a64eb |
completed | March 27, 2026, 9:32 p.m. |
Created at: March 27, 2026, 1:52 p.m.