Triple
T20669793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gyeongsang Province |
E507988
|
entity |
| Predicate | hasSubregion |
P285
|
FINISHED |
| Object | Yeongnam |
—
|
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: Yeongnam | Statement: [Gyeongsang Province, hasSubregion, Yeongnam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yeongnam Context triple: [Gyeongsang Province, hasSubregion, Yeongnam]
-
A.
Yeongnam
chosen
Yeongnam is a southeastern region of South Korea that includes major cities like Busan and Daegu and is known for its industrial centers and rich cultural heritage.
-
B.
Gyeongbuk
Gyeongbuk is a province in eastern South Korea known for its historical sites, cultural heritage, and scenic rural landscapes.
-
C.
Dongmyeong
Dongmyeong is another name for Jumong, the legendary founder and first king of the ancient Korean kingdom of Goguryeo.
-
D.
Nakchhong
Nakchhong is a traditional ritual specialist and religious officiant within the Kirat Mundhum indigenous belief system.
-
E.
Yeoncheon
Yeoncheon is a county in Gyeonggi Province, South Korea, known for its location near the Demilitarized Zone (DMZ) and its significant historical and military 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5c735048190a01cb7692928d66e |
completed | April 20, 2026, 11:24 p.m. |
Created at: April 16, 2026, 11:44 a.m.