Triple
T18180320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Fetterman |
E435262
|
entity |
| Predicate | endTimeOfPosition Mayor of Braddock, Pennsylvania |
P122423
|
FINISHED |
| Object | 2019 |
—
|
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: 2019 | Statement: [John Fetterman, endTimeOfPosition Mayor of Braddock, Pennsylvania, 2019]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: endTimeOfPosition Mayor of Braddock, Pennsylvania Context triple: [John Fetterman, endTimeOfPosition Mayor of Braddock, Pennsylvania, 2019]
-
A.
officeEndTime (Lieutenant Governor of Pennsylvania)
Indicates the time at which the Lieutenant Governor of Pennsylvania’s term in office concludes.
-
B.
endTime (presidency of Pennsylvania Railroad)
Indicates the point in time at which the presidency of the Pennsylvania Railroad concluded.
-
C.
endTime (mayor of North York)
Indicates the point in time at which a person’s tenure as mayor of North York concludes.
-
D.
termEndAsMayor
chosen
Indicates that an entity’s period of service in the role of mayor has concluded at a specified time or event.
-
E.
startTime_positionHeld_Governor of Pennsylvania
Indicates the date and time at which an individual began serving in the position of Governor of Pennsylvania.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dffa75a081908dad0dcbd736172d |
completed | April 19, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69e4331e92408190ad607ba4956a3897 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:31 a.m.