Triple
T6688055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daejeon Station |
E152149
|
entity |
| Predicate | locatedInAdministrativeTerritory |
P40
|
FINISHED |
| Object | Dong-gu, Daejeon |
E168584
|
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: Dong-gu, Daejeon | Statement: [Daejeon Station, locatedInAdministrativeTerritory, Dong-gu, Daejeon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dong-gu, Daejeon Context triple: [Daejeon Station, locatedInAdministrativeTerritory, Dong-gu, Daejeon]
-
A.
Dong District, Daegu
Dong District, Daegu is an urban administrative district in eastern Daegu, South Korea, known for its residential neighborhoods, commercial areas, and local cultural facilities.
-
B.
Dong-gu
Dong-gu is an administrative district of the metropolitan city of Ulsan in South Korea, known for its coastal location and industrial facilities.
-
C.
Dong-gu
chosen
Dong-gu is a district-level administrative area within the metropolitan city of Daejeon in South Korea.
-
D.
Jeonpo-dong
Jeonpo-dong is a neighborhood in Busan, South Korea, known for its trendy cafes, boutiques, and vibrant urban culture.
-
E.
Seo District, Daegu
Seo District is a central administrative and commercial district of Daegu, South Korea, known for its urban neighborhoods and transportation hubs.
- 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_69c687f9977c819097e7f5ada4fe522e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b14e58708190a4ba8ff1c085f160 |
completed | March 27, 2026, 4:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723b8a5288190a2fb4d956f2dc385 |
completed | March 28, 2026, 12:41 a.m. |
Created at: March 27, 2026, 2:04 p.m.