Triple
T19089338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seoul Station |
E467238
|
entity |
| Predicate | adjacentTo |
P224
|
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: [Seoul Station, adjacentTo, Namsan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namsan Context triple: [Seoul Station, adjacentTo, 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.
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.
-
D.
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.
-
E.
Samseongsan
Samseongsan is a mountain in South Korea known for its hiking trails and views over the Anyang and southern Seoul metropolitan 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e34981648190a89b006831846940 |
completed | April 20, 2026, 8:26 a.m. |
Created at: April 10, 2026, 12:04 p.m.