Triple
T34173338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger Griswold |
E876599
|
entity |
| Predicate | servedAsLieutenantGovernorEnd |
P200498
|
FINISHED |
| Object | 1811 |
—
|
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: 1811 | Statement: [Roger Griswold, servedAsLieutenantGovernorEnd, 1811]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedAsLieutenantGovernorEnd Context triple: [Roger Griswold, servedAsLieutenantGovernorEnd, 1811]
-
A.
servedAsGovernorUntil
Indicates that an entity held the position of governor up to a specified end date or time.
-
B.
servedAsLieutenantGovernorOfVirginiaFrom
Indicates that a person held the office of Lieutenant Governor of Virginia starting from a specified date or time period.
-
C.
servedAsLieutenantGovernorOfVirginiaUntil
Indicates that a person held the position of Lieutenant Governor of Virginia up to a specified end date or point in time.
-
D.
lieutenantGovernorDuringTerm
Indicates that a person served as lieutenant governor of a jurisdiction during the specified officeholder’s term in a particular office.
-
E.
succeededInOfficeAsGovernorBy
Indicates that one individual’s term as governor ended and was directly followed by another individual’s term in the same office.
- 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_69f349ad97ac8190bf1f17417c970e64 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff90b673248190b4dda9e005642d17 |
completed | May 9, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69ff8d5bee1081909274052945e98a6f |
completed | May 9, 2026, 7:39 p.m. |
| PDg | Predicate description generation | batch_69ff90b5b98881909620033d78e4a9b8 |
completed | May 9, 2026, 7:53 p.m. |
Created at: May 1, 2026, 1:54 a.m.