Triple
T20748116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jinju-si |
E510642
|
entity |
| Predicate | hasKoreanName |
P17869
|
FINISHED |
| Object | 진주시 |
—
|
NE NERFINISHED |
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: 진주시 | Statement: [Jinju-si, hasKoreanName, 진주시]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 진주시 Context triple: [Jinju-si, hasKoreanName, 진주시]
-
A.
진주
진주 is a city in South Gyeongsang Province, South Korea, known for its rich history, cultural heritage, and the annual Jinju Namgang Yudeung (Lantern) Festival.
-
B.
Jinju-si
chosen
Jinju-si is a city in South Gyeongsang Province, South Korea, known for its historic Jinju Fortress and the annual Namgang Yudeung (Lantern) Festival.
-
C.
Gijeon
Gijeon is an alternative name for the Seoul Capital Area, the densely populated metropolitan region surrounding South Korea’s capital city.
-
D.
Kwangju-si
Kwangju-si is a city in Gyeonggi Province, South Korea, known for its mix of suburban residential areas, light industry, and historical sites near the Seoul metropolitan area.
-
E.
Kyŏngju-si
Kyŏngju-si is a historic coastal city in southeastern South Korea renowned for its rich Silla Dynasty heritage, ancient temples, and numerous UNESCO World Heritage sites.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c845e88190b4c5f3ae79291182 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c226fbf881909794eff3ee9e206b |
completed | April 21, 2026, 12:17 a.m. |
Created at: April 16, 2026, 12:33 p.m.