Triple
T14886560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jongno District |
E350135
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Yeonji-dong |
E573330
|
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: Yeonji-dong | Statement: [Jongno District, contains, Yeonji-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yeonji-dong Context triple: [Jongno District, contains, Yeonji-dong]
-
A.
Yeonji-dong
Yeonji-dong is a neighborhood (dong) located within Pusanjin District in Busan, South Korea.
-
B.
Gyeonji-dong
chosen
Gyeonji-dong is a neighborhood in central Seoul, South Korea, known for its location within the historic Jongno District.
-
C.
Yeonhui-dong
Yeonhui-dong is a neighborhood in Seodaemun District, Seoul, known for its quiet residential character and proximity to major university and commercial areas like Sinchon.
-
D.
Cheonyeon-dong
Cheonyeon-dong is a neighborhood (dong) in Seoul, South Korea, known as a residential area within the central-western part of the city.
-
E.
Yeonsu-dong
Yeonsu-dong is a neighborhood within Incheon, South Korea, known as a residential and local commercial area of Yeonsu District.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5f5b1c88190815f3585770cb135 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fffee31b70819092d0583100a7101a |
completed | May 10, 2026, 3:43 a.m. |
Created at: April 10, 2026, 1:56 a.m.