Triple
T37612759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vice President of Palau |
E935831
|
entity |
| Predicate | officeHoldersTermLength |
P202104
|
FINISHED |
| Object | 4 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: 4 years | Statement: [Vice President of Palau, officeHoldersTermLength, 4 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHoldersTermLength Context triple: [Vice President of Palau, officeHoldersTermLength, 4 years]
-
A.
officeHoldersTermType
Indicates the type or category of term during which an individual holds a particular office or position.
-
B.
numberOfTermInOffice
Indicates the specific ordinal count of how many terms an entity has served in a particular office or position.
-
C.
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.
-
D.
headOfStateTermLength
Indicates the duration of time that a person serves in the role of head of state for a given political entity.
-
E.
officeHoldersNumberPerTerm
Indicates the number of individuals who hold a given office during a single specified term.
- 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_69f76ed16b748190ad6add183b1be688 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a00512437d48190ad20324968ead5f4 |
completed | May 10, 2026, 9:34 a.m. |
| PD | Predicate disambiguation | batch_6a0050227350819099f41369c3d168be |
completed | May 10, 2026, 9:30 a.m. |
| PDg | Predicate description generation | batch_6a0051234cc08190adae6e2cfae2f8cc |
completed | May 10, 2026, 9:34 a.m. |
Created at: May 3, 2026, 4:18 p.m.