Triple
T18979057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hallasan |
E464372
|
entity |
| Predicate | hasPeak |
P8205
|
FINISHED |
| Object | Baengnokdam rim |
—
|
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: Baengnokdam rim | Statement: [Hallasan, hasPeak, Baengnokdam rim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baengnokdam rim Context triple: [Hallasan, hasPeak, Baengnokdam rim]
-
A.
Yudeungcheon
Yudeungcheon is a river in Daejeon, South Korea, known for flowing through the city’s urban areas and serving as a local recreational and ecological space.
-
B.
Baengnokdam
chosen
Baengnokdam is the scenic volcanic crater lake at the summit of Hallasan on Jeju Island, South Korea, renowned for its dramatic landscape and cultural significance.
-
C.
Myeongneung
Myeongneung is one of the royal burial sites from Korea’s Joseon Dynasty, forming part of the UNESCO-listed Royal Tombs complex.
-
D.
Gye-dong
Gye-dong is a historic neighborhood in central Seoul, South Korea, known for its traditional hanok houses and cultural heritage sites.
-
E.
Odaesan
Odaesan is a prominent mountain in South Korea known for its scenic national park, rich biodiversity, and important Buddhist temples such as Woljeongsa.
- 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d621e3e08190b2d1d969ecaa380b |
completed | April 20, 2026, 7:30 a.m. |
Created at: April 10, 2026, 12:01 p.m.