Triple
T4749843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oh Se-hoon |
E105450
|
entity |
| Predicate | hasPublicOfficeRank |
P32760
|
FINISHED |
| Object | metropolitan mayor |
—
|
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: metropolitan mayor | Statement: [Oh Se-hoon, hasPublicOfficeRank, metropolitan mayor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPublicOfficeRank Context triple: [Oh Se-hoon, hasPublicOfficeRank, metropolitan mayor]
-
A.
isPoliticalOffice
Indicates that the subject is a formal governmental or political position held within a public institution or authority.
-
B.
hasPoliticalOfficeScope
Indicates that a political office or position is limited to, defined within, or applicable to a specific jurisdiction, level, or scope of political authority.
-
C.
hasMinisterialRank
Indicates that an entity holds a position or status equivalent to a government minister in rank.
-
D.
rankHeldByOfficeholder
chosen
Indicates the specific rank or level associated with an office or position that is held by a particular officeholder.
-
E.
hasOffice
Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
- F. None of above.
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_69bd43f07fa48190954317d01600994a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64c83af48190bd57be79c1505e9d |
completed | March 20, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69bd6223defc8190823665a6592c1154 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:20 p.m.