Triple
T6845389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nam District, Daegu |
E157880
|
entity |
| Predicate | isAdministrativeUnit |
P73475
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Nam District, Daegu, isAdministrativeUnit, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAdministrativeUnit Context triple: [Nam District, Daegu, isAdministrativeUnit, true]
-
A.
hasAdministrativeUnit
Indicates that one entity possesses, contains, or is associated with another entity that functions as its administrative subdivision or governing unit.
-
B.
isAdministrativeUnitWithin
Indicates that one administrative unit is geographically or jurisdictionally contained within another administrative unit.
-
C.
representsAdministrativeUnit
Indicates that one entity serves as or corresponds to the administrative unit governing or organizing another entity.
-
D.
administrativeUnitType
Indicates the specific kind or category of administrative unit involved in the relationship (e.g., city, county, province).
-
E.
laterAdministrativeUnit
Indicates that one administrative unit succeeds or replaces another in time, coming into effect at a later date.
- F. None of above. chosen
Provenance (4 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_69c6882ed4c081909dc465a7cf8838be |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d7ca96008190ba79563c2a9a9b0e |
completed | March 27, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69c6d09f90648190bc0a462c7d59de1b |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d623aba88190a93ec9c83508c960 |
completed | March 27, 2026, 7:10 p.m. |
Created at: March 27, 2026, 2:19 p.m.