Triple
T29359412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Mifflin |
E744543
|
entity |
| Predicate | endTimeOfPosition Governor of Pennsylvania |
P172224
|
FINISHED |
| Object | 1799 |
—
|
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: 1799 | Statement: [Thomas Mifflin, endTimeOfPosition Governor of Pennsylvania, 1799]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: endTimeOfPosition Governor of Pennsylvania Context triple: [Thomas Mifflin, endTimeOfPosition Governor of Pennsylvania, 1799]
-
A.
startTime_positionHeld_Governor of Pennsylvania
Indicates the date and time at which an individual began serving in the position of Governor of Pennsylvania.
-
B.
officeEndTime (Lieutenant Governor of Pennsylvania)
Indicates the time at which the Lieutenant Governor of Pennsylvania’s term in office concludes.
-
C.
termEndAsGovernorOfPennsylvania
chosen
Indicates that an entity’s tenure in the office of Governor of Pennsylvania has concluded.
-
D.
succeededBy (Governor of Pennsylvania)
Indicates that one individual directly follows another in holding the office of Governor of Pennsylvania.
-
E.
officeStartTime (Lieutenant Governor of Pennsylvania)
Indicates the time at which the Lieutenant Governor of Pennsylvania officially begins their term in office.
- 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_69f0a79aee588190b490f19d93c6e52d |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: April 28, 2026, 2:16 p.m.