Triple
T21584639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mapo District |
E532616
|
entity |
| Predicate | Romanization |
P2508
|
FINISHED |
| Object | Mapo-gu |
—
|
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: Mapo-gu | Statement: [Mapo District, Romanization, Mapo-gu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mapo-gu Context triple: [Mapo District, Romanization, Mapo-gu]
-
A.
Mapo-gu
chosen
Mapo-gu is a district in western Seoul, South Korea, known for its vibrant Hongdae area, cultural venues, and riverside parks along the Han River.
-
B.
Jung-gu
Jung-gu is a central urban district name used in several major South Korean cities, typically encompassing key commercial, administrative, and cultural areas.
-
C.
Jung-gu
Jung-gu is a central administrative district of the metropolitan city of Ulsan in South Korea.
-
D.
Jung-gu
Jung-gu is a central urban district of Daegu, South Korea, known for its dense commercial areas, historic sites, and administrative importance.
-
E.
Jung-gu
Jung-gu is a central district of Seoul, South Korea, known as a major hub for business, shopping, and historic sites.
- 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_69e0c4618bec8190bcb0feb74568cbb1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eeeb5f2cc0819095552de70eb2ad8d |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 16, 2026, 6:31 p.m.