Triple
T22309633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myeongdong |
E551477
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Namsan |
—
|
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: Namsan | Statement: [Myeongdong, near, Namsan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namsan Context triple: [Myeongdong, near, Namsan]
-
A.
Namsan
chosen
Namsan is a prominent central mountain in Seoul, South Korea, known for its panoramic city views and the iconic N Seoul Tower.
-
B.
Dobongsan
Dobongsan is a prominent, rocky mountain in northern South Korea known for its scenic hiking trails, granite peaks, and location within Bukhansan National Park.
-
C.
Mount Namsan
Mount Namsan is a historically significant mountain in Gyeongju, South Korea, renowned for its numerous ancient Buddhist relics, temples, and archaeological sites.
-
D.
Gwanak Mountain
Gwanak Mountain is a prominent peak in southern Seoul, South Korea, known for its hiking trails, scenic views, and cultural sites such as temples and hermitages.
-
E.
Gwanggyo Mountain
Gwanggyo Mountain is a prominent natural landmark in South Korea known for its hiking trails and scenic views near the city of Suwon.
- 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_69e11e46c0188190800181a4233f28fe |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1574d53148190a1ec07f849e1ae9d |
completed | April 29, 2026, 12:56 a.m. |
Created at: April 16, 2026, 8:42 p.m.