Triple
T34094419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vice Governor of Negros Occidental |
E874384
|
entity |
| Predicate | maximumConsecutiveYearsInOffice |
P182533
|
FINISHED |
| Object | 9 years |
—
|
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: 9 years | Statement: [Vice Governor of Negros Occidental, maximumConsecutiveYearsInOffice, 9 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumConsecutiveYearsInOffice Context triple: [Vice Governor of Negros Occidental, maximumConsecutiveYearsInOffice, 9 years]
-
A.
numberOfTermInOffice
Indicates the specific ordinal count of how many terms an entity has served in a particular office or position.
-
B.
yearsInPower
chosen
Indicates the duration, typically in years, that an entity has held a position of authority or control.
-
C.
numberOfTimesInOffice
Indicates the count of separate terms or periods an entity has held a particular office or position.
-
D.
termOfOfficeResult
Indicates the outcome or status associated with a specific term of office, such as whether it was completed, successful, or ended in a particular way.
-
E.
presidentialTerm
Indicates the period of time during which an individual officially serves as president of a country or 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 1, 2026, 1:52 a.m.