Triple
T20095958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daechi-dong |
E496399
|
entity |
| Predicate | romanization |
P2508
|
FINISHED |
| Object | Daechi-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: Daechi-dong | Statement: [Daechi-dong, romanization, Daechi-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daechi-dong Context triple: [Daechi-dong, romanization, Daechi-dong]
-
A.
Daechi-dong
chosen
Daechi-dong is a wealthy neighborhood in Seoul renowned for its dense concentration of private academies and highly competitive educational culture.
-
B.
Daecheong-dong
Daecheong-dong is a neighborhood in central Busan, South Korea, known for its urban setting within the city's Jung District.
-
C.
Deungchon-dong
Deungchon-dong is a neighborhood in Seoul, South Korea, known for its residential areas, local markets, and convenient urban amenities.
-
D.
Seongho-dong
Seongho-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
E.
Samcheong-dong
Samcheong-dong is a picturesque neighborhood in central Seoul known for its traditional hanok houses, art galleries, cafes, and proximity to historic palaces.
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6666cc02481908780a415b19c05a2 |
completed | April 20, 2026, 5:46 p.m. |
Created at: April 11, 2026, 11:25 p.m.