Triple
T766328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Board of Governors of the United States Postal Service |
E16182
|
entity |
| Predicate | numberOfPresidentiallyAppointedGovernors |
P5523
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Board of Governors of the United States Postal Service, numberOfPresidentiallyAppointedGovernors, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPresidentiallyAppointedGovernors Context triple: [Board of Governors of the United States Postal Service, numberOfPresidentiallyAppointedGovernors, 9]
-
A.
numberOfGovernors
chosen
Indicates the total count of governors associated with or governing a specified entity.
-
B.
numberOfTermsAsGovernor
Indicates the number of separate terms an individual has served in the role of governor.
-
C.
numberOfPresidents
Indicates the total count of individuals who have held the position of president for a given entity or within a specified context.
-
D.
notableGovernor
Indicates that an individual has served as a governor in a way considered historically or socially significant.
-
E.
hasPresident
Indicates that an entity holds the position or role of president for another entity.
- 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_69a493684ee48190bd43b7c78da4aec8 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a765ba688190ab328bb159583077 |
completed | March 1, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69a4a5074c788190a74fc20ad24e2d26 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.