Triple
T20258032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Chungcheong Province |
E498754
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Nonsan |
—
|
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: Nonsan | Statement: [South Chungcheong Province, hasMajorCity, Nonsan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nonsan Context triple: [South Chungcheong Province, hasMajorCity, Nonsan]
-
A.
Nonsan
chosen
Nonsan is a city in South Chungcheong Province, South Korea, known for its agricultural production and military training facilities.
-
B.
Nonsan-si
Nonsan-si is a city in South Chungcheong Province, South Korea, known for its agricultural production and military training facilities.
-
C.
Nantai-san
Nantai-san is a sacred volcanic mountain in Japan’s Nikkō region, revered in Shinto tradition and known for its scenic hiking trails and religious significance.
-
D.
Nuriro
Nuriro is a class of South Korean intercity passenger trains operated by Korail, providing medium-speed rail services on various routes.
-
E.
Ninpei
Ninpei was a Japanese era (nengō) of the late Heian period, spanning the reign of Emperor Toba and used to mark years in imperial court records and documents.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674c7296c819092860942de8f28d5 |
completed | April 20, 2026, 6:47 p.m. |
Created at: April 11, 2026, 11:41 p.m.