Triple
T7803173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seomyeon underground shopping center |
E180481
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Seomyeon |
E252412
|
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: Seomyeon | Statement: [Seomyeon underground shopping center, locatedIn, Seomyeon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seomyeon Context triple: [Seomyeon underground shopping center, locatedIn, Seomyeon]
-
A.
Seomyeon
chosen
Seomyeon is a major commercial and entertainment hub in central Busan, South Korea, known for its dense concentration of shops, restaurants, bars, and nightlife.
-
B.
Yangjeong-dong
Yangjeong-dong is a neighborhood (dong) located within Busanjin District in the city of Busan, South Korea.
-
C.
Yeouido-dong
Yeouido-dong is a major financial and business district in Seoul, South Korea, known for its skyscrapers, corporate headquarters, and role as a political and economic hub.
-
D.
Seocho-dong
Seocho-dong is a neighborhood in southern Seoul, South Korea, known for its affluent residential areas, major cultural venues, and proximity to key business districts.
-
E.
Cheongnyang-eup
Cheongnyang-eup is a town-level administrative division located within Ulju County in Ulsan, South Korea.
- 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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf635a4648190af907a686d87f073 |
completed | March 30, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc55d5650c8190862d89d1dcc488b4 |
completed | March 31, 2026, 11:16 p.m. |
Created at: March 30, 2026, 4:34 p.m.