Triple
T766329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Board of Governors of the United States Postal Service |
E16182
|
entity |
| Predicate | numberOfExOfficioMembers |
P19683
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Board of Governors of the United States Postal Service, numberOfExOfficioMembers, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfExOfficioMembers Context triple: [Board of Governors of the United States Postal Service, numberOfExOfficioMembers, 2]
-
A.
numberOfCommitteeMembers
Indicates the total count of individuals who are members of a given committee.
-
B.
numberOfPermanentMembers
Indicates the total count of entities that hold permanent membership within a specified group or organization.
-
C.
numberOfCabinetMembers
Indicates the total count of cabinet members associated with a given government, administration, or leader.
-
D.
numberOfNonPermanentMembers
Indicates the count of entities that hold non-permanent (temporary or rotating) membership within a larger group or body.
-
E.
numberOfBoardMembers
Indicates the total count of individuals who serve as members on a board.
- 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_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. |
| PDg | Predicate description generation | batch_69a4a7648a6c8190a9051a3d177ff7e2 |
completed | March 1, 2026, 8:53 p.m. |
Created at: March 1, 2026, 7:37 p.m.