Triple
T6535337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yeongdodaegyo Bridge |
E152344
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object | City of Busan |
E4279
|
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: City of Busan | Statement: [Yeongdodaegyo Bridge, owner, City of Busan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Busan Context triple: [Yeongdodaegyo Bridge, owner, City of Busan]
-
A.
Pohang
Pohang is a major industrial and port city in South Korea, best known as the home of the global steelmaker POSCO and a key hub on the country’s east coast.
-
B.
Busan
chosen
Busan is South Korea’s second-largest city and a major international port known for its bustling harbor, beaches, and coastal scenery.
-
C.
Jinju-si
Jinju-si is a city in South Gyeongsang Province, South Korea, known for its historic Jinju Fortress and the annual Namgang Yudeung (Lantern) Festival.
-
D.
Changwon
Changwon is a major industrial and administrative city in South Gyeongsang Province, South Korea, known for its planned urban layout and role as a regional government and manufacturing hub.
-
E.
Gimcheon
Gimcheon is a city in North Gyeongsang Province, South Korea, known as a regional transportation hub and administrative center.
- 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_69c7eeb127248190bbee7a9f69c2b980 |
completed | March 28, 2026, 3:07 p.m. |
Created at: March 27, 2026, 1:46 p.m.