Triple
T23068615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jongno-gu |
E575125
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Jongno |
—
|
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: Jongno | Statement: [Jongno-gu, namedAfter, Jongno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jongno Context triple: [Jongno-gu, namedAfter, Jongno]
-
A.
Cheongdam-dong
Cheongdam-dong is an affluent neighborhood in Seoul known for its luxury boutiques, high-end residences, and trendy cafes and galleries.
-
B.
Jongno District
chosen
Jongno District is a central historic and administrative area of Seoul, South Korea, known for its government institutions, cultural landmarks, and traditional neighborhoods.
-
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.
Taepyeongno
Taepyeongno is a major thoroughfare and business district in central Seoul, South Korea, known for its government buildings, corporate offices, and proximity to key civic landmarks.
-
E.
Myeongdong
Myeongdong is a major shopping and entertainment district in central Seoul, famous for its fashion boutiques, street food, and vibrant nightlife.
- 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_69e245bd6e4c8190bb8942245b68cad5 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f189a5aa4081909b3f0dc92877323d |
completed | April 29, 2026, 4:31 a.m. |
Created at: April 17, 2026, 3:55 p.m.