Triple
T11325298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaya-dong |
E268196
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Busanjin-gu |
E34080
|
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: Busanjin-gu | Statement: [Gaya-dong, partOf, Busanjin-gu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Busanjin-gu Context triple: [Gaya-dong, partOf, Busanjin-gu]
-
A.
Busanjin District
chosen
Busanjin District is a central urban district of Busan, South Korea, known as a major commercial and transportation hub of the city.
-
B.
Pusanjin-gu
Pusanjin-gu is a central urban district of Busan, South Korea, known for its major commercial areas, transportation hubs, and dense residential neighborhoods.
-
C.
Busan Jung District
Busan Jung District is a central urban district of Busan, South Korea, known for its historic downtown area, bustling commercial streets, and major shopping and cultural attractions.
-
D.
Deogyang-gu
Deogyang-gu is a district of the city of Goyang in Gyeonggi Province, South Korea, known for its residential areas, historical sites, and proximity to Seoul.
-
E.
Geumjeong-gu
Geumjeong-gu is a district in Busan, South Korea, known for its residential areas, transportation hubs, and proximity to Geumjeongsan Mountain.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9e2253881909518cad0f12ef612 |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f470faab4c8190ac9091713080dc7a |
completed | May 1, 2026, 9:23 a.m. |
Created at: April 8, 2026, 9:32 p.m.