Triple
T24050195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan McKee |
E595632
|
entity |
| Predicate | servedAsLieutenantGovernorUnder |
P209
|
FINISHED |
| Object | Gina Raimondo |
—
|
NE NERFINISHED |
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: Gina Raimondo | Statement: [Dan McKee, servedAsLieutenantGovernorUnder, Gina Raimondo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedAsLieutenantGovernorUnder Context triple: [Dan McKee, servedAsLieutenantGovernorUnder, Gina Raimondo]
-
A.
succeededInOfficeAsGovernorBy
Indicates that one individual’s term as governor ended and was directly followed by another individual’s term in the same office.
-
B.
precededInOfficeAsGovernorBy
Indicates that one individual assumed the role of governor after another specific individual, who held the office immediately before them.
-
C.
hasLieutenantGovernor
chosen
Indicates that one entity serves as the lieutenant governor of another entity (typically a state, province, or territory).
-
D.
laterGovernor
Indicates that one entity subsequently became the governor of a place or jurisdiction associated with another entity.
-
E.
servedAsGovernorUntil
Indicates that an entity held the position of governor up to a specified end date or time.
- 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_69e288c184b081909f1f1751fb8e299a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d9cfb914819091a3378518f9f28d |
completed | April 29, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:20 p.m.