Triple
T6535364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jagalchi Sijang |
E152345
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Nampo-dong |
E605668
|
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: Nampo-dong | Statement: [Jagalchi Sijang, locatedNear, Nampo-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nampo-dong Context triple: [Jagalchi Sijang, locatedNear, Nampo-dong]
-
A.
Nampo-dong
chosen
Nampo-dong is a bustling commercial and shopping district in central Busan, South Korea, known for its markets, street food, and proximity to the city’s harbor.
-
B.
Nopo-dong
Nopo-dong is a neighborhood in Busan, South Korea, known as a major transportation hub and gateway to the city.
-
C.
Mansudae district
Mansudae district is a central area of Pyongyang, North Korea, known for its major political monuments, cultural institutions, and prominent artistic facilities.
-
D.
Taedonggang District
Taedonggang District is an administrative district of Pyongyang, North Korea, known for hosting major political monuments and government-related sites.
-
E.
Pyongchon District
Pyongchon District is a central urban district of Pyongyang, North Korea, known for its industrial facilities and major national institutions.
- 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_69c688048ec8819093a47f7d332e12ec |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6adc05da88190b402085954cec8e0 |
completed | March 27, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6eed0ef548190b384e37f39830b14 |
completed | March 27, 2026, 8:55 p.m. |
Created at: March 27, 2026, 1:46 p.m.