Triple
T19881818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Namsan |
E477792
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Myeong-dong |
—
|
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: Myeong-dong | Statement: [Namsan, locatedNear, Myeong-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Myeong-dong Context triple: [Namsan, locatedNear, Myeong-dong]
-
A.
Myeongdong
chosen
Myeongdong is a major shopping and entertainment district in central Seoul, famous for its fashion boutiques, street food, and vibrant nightlife.
-
B.
Cheongdam-dong
Cheongdam-dong is an affluent neighborhood in Seoul known for its luxury boutiques, high-end residences, and trendy cafes and galleries.
-
C.
Cheongun-dong
Cheongun-dong is a neighborhood in central Seoul, South Korea, known for its proximity to historic sites such as Gyeongbokgung Palace and the Blue House.
-
D.
Cheongnyong-dong
Cheongnyong-dong is a neighborhood located within Geumjeong District in Busan, South Korea.
-
E.
Yangjeong-dong
Yangjeong-dong is a neighborhood (dong) located within Busanjin District in the city of Busan, South Korea.
- 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658df3f5c81909b5b290de91b8d50 |
completed | April 20, 2026, 4:48 p.m. |
Created at: April 10, 2026, 1:52 p.m.