Triple
T35369693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rena Haley |
E1021733
|
entity |
| Predicate | motherHeldOffice |
P127245
|
FINISHED |
| Object | Governor of South Carolina |
—
|
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: Governor of South Carolina | Statement: [Rena Haley, motherHeldOffice, Governor of South Carolina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: motherHeldOffice Context triple: [Rena Haley, motherHeldOffice, Governor of South Carolina]
-
A.
motherPoliticalRole
chosen
Indicates that an individual’s mother holds or held a specific political office or role.
-
B.
memberHeldOfficeFrom
Indicates that a member began holding a particular office or position starting from a specified date or time.
-
C.
heldPoliticalOfficeIn
Indicates that an entity served in a political office or position within a specified governmental body or jurisdiction.
-
D.
officeHoldersWere
Indicates that certain individuals held specific offices or positions during a particular time or context.
-
E.
possibleOfficeHeld
Indicates that an entity may have held, or is a candidate to have held, a particular office or position, without asserting it as a confirmed fact.
- 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_69f76df000488190ab7c97f565677055 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.