Triple
T19122538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeongbang Waterfall |
E468083
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Seogwipo |
—
|
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: Seogwipo | Statement: [Jeongbang Waterfall, locatedIn, Seogwipo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seogwipo Context triple: [Jeongbang Waterfall, locatedIn, Seogwipo]
-
A.
Seogwipo
chosen
Seogwipo is a coastal city on South Korea’s Jeju Island known for its waterfalls, volcanic landscapes, and popular tourist attractions.
-
B.
Odaesan
Odaesan is a prominent mountain in South Korea known for its scenic national park, rich biodiversity, and important Buddhist temples such as Woljeongsa.
-
C.
Taebong
Taebong was a short-lived Korean kingdom of the early 10th century that emerged during the Later Three Kingdoms period before being absorbed by Goryeo.
-
D.
Hwaseong
Hwaseong is a city in Gyeonggi Province, South Korea, known for its rapid industrial growth and proximity to major urban centers like Suwon and Seoul.
-
E.
Tancheon
Tancheon is a river in South Korea that flows through the city of Seongnam and serves as a key urban waterway and recreational area.
- 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3c9dfcc819090f8424608892cb3 |
completed | April 20, 2026, 8:28 a.m. |
Created at: April 10, 2026, 12:05 p.m.