Triple
T27807749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hsu Shui-teh as Mayor of Taipei |
E702428
|
entity |
| Predicate | officeHolderCitizenship |
P17302
|
FINISHED |
| Object | Taiwanese |
—
|
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: Taiwanese | Statement: [Hsu Shui-teh as Mayor of Taipei, officeHolderCitizenship, Taiwanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHolderCitizenship Context triple: [Hsu Shui-teh as Mayor of Taipei, officeHolderCitizenship, Taiwanese]
-
A.
officeHolderNationality
chosen
Indicates that the nationality of an office holder is a specified country or nation.
-
B.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
-
C.
officeHolderIs
Indicates that one entity serves as the office holder (e.g., official or position occupant) of another entity, such as an office, role, or institution.
-
D.
officeHolderOccupation
Indicates that the occupation describes the role or job held by an office holder.
-
E.
officeHolderTypicallyFrom
Indicates that the person holding a particular office is typically drawn from or originates from a specified group, region, or category.
- 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_69ef840a16748190926719ab96120bae |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
Created at: April 27, 2026, 5:40 p.m.