Triple
T17669786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commissioner of the Federal Communications Commission |
E440488
|
entity |
| Predicate | maximumNumberOfCommissioners |
P128487
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Commissioner of the Federal Communications Commission, maximumNumberOfCommissioners, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumNumberOfCommissioners Context triple: [Commissioner of the Federal Communications Commission, maximumNumberOfCommissioners, 5]
-
A.
numberOfCommissioners
Indicates the specific count of commissioners associated with a given entity or context.
-
B.
numberOfResidentCommissioners
Indicates the quantity of resident commissioners associated with a given entity.
-
C.
numberOfDelegates
Indicates the quantity of delegates associated with or assigned to a particular entity or event.
-
D.
maximumNumberOfJustices
Indicates the total number of justices that is allowed or prescribed as the upper limit for a given judicial body.
-
E.
numberOfAppointedMembers
Indicates the specific count of members who have been formally appointed to a group, body, or position.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f67f6188190a978c7c9f462064d |
completed | April 19, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69e3cde007d8819090dd92eea9f022cc |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 9:59 a.m.