Triple
T14089001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jung District, Seoul |
E339072
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Namsan Mountain |
E477792
|
NE FINISHED |
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 Mountain | Statement: [Jung District, Seoul, contains, Namsan Mountain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namsan Mountain Context triple: [Jung District, Seoul, contains, Namsan Mountain]
-
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.
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.
-
C.
Hwangnyeongsan Mountain
Hwangnyeongsan Mountain is a prominent peak in Busan, South Korea, known for its panoramic city and coastal views, especially popular at night.
-
D.
Geumjeongsan
Geumjeongsan is a prominent mountain in Busan, South Korea, known for its scenic hiking trails, historic fortress walls, and cultural sites.
-
E.
Ok-dong
Ok-dong is a neighborhood in Ulsan, South Korea, known for encompassing the large urban green space of Ulsan Grand Park.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5ee1ce88819091c983286289337e |
completed | April 14, 2026, 3:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdefe88b481908b3dca1f019e7809 |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:21 p.m.