Triple
T20557059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sacheon Airport |
E504745
|
entity |
| Predicate | hasCityServed |
P3936
|
FINISHED |
| Object | Goseong County |
—
|
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: Goseong County | Statement: [Sacheon Airport, hasCityServed, Goseong County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goseong County Context triple: [Sacheon Airport, hasCityServed, Goseong County]
-
A.
Goseong County
chosen
Goseong County is a coastal county in Gangwon Province, South Korea, known for its scenic East Sea shoreline, historical sites, and proximity to the Demilitarized Zone (DMZ).
-
B.
Yeongwol County
Yeongwol County is a rural county in Gangwon Province, South Korea, known for its scenic river valleys, historical sites, and cultural heritage.
-
C.
Seongju County
Seongju County is a rural administrative region in southeastern South Korea known for its melon farming and traditional cultural heritage.
-
D.
Hwacheon County
Hwacheon County is a rural county in Gangwon Province, South Korea, known for its mountainous terrain, lakes, and popular ice fishing festival.
-
E.
Yeoncheon County
Yeoncheon County is a rural county in Gyeonggi Province, South Korea, known for its location near the Demilitarized Zone (DMZ) and its historical military significance.
- 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a5de9c008190b8620628fb285e90 |
completed | April 20, 2026, 10:17 p.m. |
Created at: April 16, 2026, 11:38 a.m.