Triple
T18125359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Icheon |
E433858
|
entity |
| Predicate | romanization |
P2508
|
FINISHED |
| Object | Icheon-si |
—
|
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: Icheon-si | Statement: [Icheon, romanization, Icheon-si]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Icheon-si Context triple: [Icheon, romanization, Icheon-si]
-
A.
Icheon
chosen
Icheon is a South Korean city renowned for its traditional ceramics and hot spring resorts.
-
B.
Hwaseong-si
Hwaseong-si is a rapidly growing city in Gyeonggi Province, South Korea, known for its industrial complexes, coastal wetlands, and proximity to Seoul.
-
C.
Jecheon
Jecheon is a city in North Chungcheong Province, South Korea, known as a regional transport hub surrounded by mountains and lakes.
-
D.
Siheung
Siheung is a coastal city in northwestern South Korea known for its industrial complexes, wetlands, and proximity to Seoul.
-
E.
Anseong
Anseong is a city in Gyeonggi Province, South Korea, known for its traditional culture, agricultural heritage, and annual Baudeogi 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dded1bd4819080fa362e88c921cf |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:29 a.m.