Triple
T6731860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John C. Frémont |
E153651
|
entity |
| Predicate | startTimeOfOfficeHeld |
P18957
|
FINISHED |
| Object | United States Senator from California, 1850 |
—
|
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: United States Senator from California, 1850 | Statement: [John C. Frémont, startTimeOfOfficeHeld, United States Senator from California, 1850]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTimeOfOfficeHeld Context triple: [John C. Frémont, startTimeOfOfficeHeld, United States Senator from California, 1850]
-
A.
officeHolderStartTime
Indicates the date and time at which an individual begins holding a particular office or position.
-
B.
timeInOfficeBeginsIn
chosen
Indicates the point in time or date when an entity’s term, tenure, or period in office starts.
-
C.
lastOfficeHolderStartDate
Indicates the date on which the most recent person to hold a particular office or position began their term.
-
D.
termInOffice
Indicates the period during which an individual officially holds a particular office or position.
-
E.
inauguralHolderStartDate
Indicates the date on which the first person or entity to hold a position, title, or role officially began their tenure.
- 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d354177481908ab3cf5437c095e2 |
completed | March 27, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69c6d08e8a2c8190ae4e8d8c039be7ce |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:09 p.m.