Triple
T1688065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yeonje District |
E36486
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Busanjin District |
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 District | Statement: [Yeonje District, borderedBy, Busanjin District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Busanjin District Context triple: [Yeonje District, borderedBy, Busanjin District]
-
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.
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.
-
C.
Dongnae District
Dongnae District is a historic and central administrative district of Busan, South Korea, known for its hot springs and cultural heritage sites.
-
D.
Bupyeong District
Bupyeong District is a populous urban district of Incheon, South Korea, known as a major residential, commercial, and transportation hub in the metropolitan area.
-
E.
Suyeong District
Suyeong District is an urban coastal district in Busan, South Korea, known for its beaches, residential areas, and cultural attractions.
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6294f5ac819089cf5c2530ec71a0 |
completed | March 6, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1eec2a3f081909aa9f32ff5537a3c |
completed | March 11, 2026, 10:37 p.m. |
Created at: March 4, 2026, 7:29 p.m.