Triple
T20669742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 진주 |
E507987
|
entity |
| Predicate | hasMajorRiver |
P165
|
FINISHED |
| Object | Namgang |
—
|
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: Namgang | Statement: [진주, hasMajorRiver, Namgang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namgang Context triple: [진주, hasMajorRiver, Namgang]
-
A.
Namgang
chosen
Namgang is a river in South Korea known as a major tributary of the Nakdong River, flowing through cities such as Jinju.
-
B.
Dongmyeong
Dongmyeong is another name for Jumong, the legendary founder and first king of the ancient Korean kingdom of Goguryeo.
-
C.
Nakchhong
Nakchhong is a traditional ritual specialist and religious officiant within the Kirat Mundhum indigenous belief system.
-
D.
Sungneung
Sungneung is a royal Joseon Dynasty tomb located within the Donggureung burial complex in South Korea.
-
E.
Suwoncheon
Suwoncheon is a stream running through the city of Suwon in South Korea, known for flowing past the historic Hwaseong Fortress and serving as a key feature of the local urban landscape.
- 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.