Triple
T16092311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dangjin |
E390386
|
entity |
| Predicate | revisedRomanization |
P23170
|
FINISHED |
| Object | Dangjin-si |
E390386
|
NE FINISHED |
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: Dangjin-si | Statement: [Dangjin, revisedRomanization, Dangjin-si]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dangjin-si Context triple: [Dangjin, revisedRomanization, Dangjin-si]
-
A.
Dangjin
chosen
Dangjin is a coastal city in South Chungcheong Province, South Korea, known for its heavy industry, steel production, and port facilities on the Yellow Sea.
-
B.
Icheon
Icheon is a South Korean city renowned for its traditional ceramics and hot spring resorts.
-
C.
Kŏje-si
Kŏje-si is the McCune–Reischauer romanization of Geoje, a city in South Gyeongsang Province, South Korea, known for its shipbuilding industry and scenic coastal landscapes.
-
D.
Yeongcheon
Yeongcheon is a city in southeastern South Korea known for its agricultural production and historical sites within North Gyeongsang Province.
-
E.
Jincheon
Jincheon is a county in North Chungcheong Province, South Korea, known for its agricultural production and growing role as a logistics and industrial hub.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1858d1264819099434d7201614d05 |
completed | April 17, 2026, 12:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff79a96d08190af69cbb18037f66e |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 4:59 a.m.