Triple
T5575210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jongno-gu |
E146300
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Yongsan-gu |
E504227
|
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: Yongsan-gu | Statement: [Jongno-gu, borderedBy, Yongsan-gu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yongsan-gu Context triple: [Jongno-gu, borderedBy, Yongsan-gu]
-
A.
Yongsan-gu
chosen
Yongsan-gu is a central district of Seoul, South Korea, known for its diverse neighborhoods, major transportation hubs, and significant commercial and cultural centers.
-
B.
Chongno-gu
Chongno-gu is a central district in Seoul, South Korea, known as the historic and cultural heart of the city, home to major palaces, government institutions, and traditional markets.
-
C.
Eunpyeong-gu
Eunpyeong-gu is a district in northwestern Seoul, South Korea, known for its mix of urban residential areas and access to nearby mountains and temples.
-
D.
Jung-gu
Jung-gu is a central district of the metropolitan city of Daejeon in South Korea, known for its mix of commercial, residential, and administrative areas.
-
E.
Jung-gu
Jung-gu is a central administrative district of the metropolitan city of Ulsan in South Korea.
- 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02067e8d8819090a006cb266da5fe |
completed | March 22, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c603c0c8388190b39b2e20c9a02f19 |
completed | March 27, 2026, 4:12 a.m. |
Created at: March 22, 2026, 3:37 p.m.