Triple
T10323900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steven Yeun |
E242709
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Seoul, South Korea |
E19209
|
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: Seoul, South Korea | Statement: [Steven Yeun, placeOfBirth, Seoul, South Korea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seoul, South Korea Context triple: [Steven Yeun, placeOfBirth, Seoul, South Korea]
-
A.
Inchon, South Korea
Inchon, South Korea is a major port city near Seoul known for its strategic coastal location and as the site of the pivotal Korean War amphibious landing.
-
B.
Suwon, South Korea
Suwon, South Korea is a major city just south of Seoul known for its high-tech industry and the UNESCO-listed Hwaseong Fortress.
-
C.
Jinju, South Korea
Jinju, South Korea is a historic city in South Gyeongsang Province known for its riverside fortress, role in the Imjin War, and annual lantern festival.
-
D.
Seoul
chosen
Seoul is the capital and largest metropolis of South Korea, known as a major global center for technology, culture, and finance.
-
E.
Osan, South Korea
Osan is a city in Gyeonggi Province, South Korea, known for its proximity to Osan Air Base and its role as a transportation and commercial hub south of Seoul.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d6ce683c8190bf5385dd04bf2de8 |
completed | April 7, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fb69410c81909b33e44a04ab77d9 |
completed | April 9, 2026, 7:18 p.m. |
Created at: April 6, 2026, 11:51 a.m.