Triple
T20669778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gyeongsang Province |
E507988
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Gyeongju |
—
|
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: Gyeongju | Statement: [Gyeongsang Province, namedAfter, Gyeongju]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gyeongju Context triple: [Gyeongsang Province, namedAfter, Gyeongju]
-
A.
Gyeongju
chosen
Gyeongju is a historic city in South Korea famed for its rich cultural heritage and numerous archaeological sites from the ancient Silla Kingdom.
-
B.
Yeongju
Yeongju is a city in eastern South Korea known for its historic temples, Confucian academies, and scenic mountainous landscapes.
-
C.
Gongju
Gongju is a historic city in South Korea that once served as the capital of the ancient Baekje Kingdom and is renowned for its rich archaeological heritage.
-
D.
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.
-
E.
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.
- 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.