Triple
T18302827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chair of the Federal Communications Commission |
E438396
|
entity |
| Predicate | numberOfCommissionersIncludingChair |
P21525
|
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: [Chair of the Federal Communications Commission, numberOfCommissionersIncludingChair, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCommissionersIncludingChair Context triple: [Chair of the Federal Communications Commission, numberOfCommissionersIncludingChair, 5]
-
A.
numberOfCommissioners
chosen
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.
numberOfCommitteeMembers
Indicates the total count of individuals who are members of a given committee.
-
D.
maximumNumberOfCommissioners
Indicates the upper limit on how many commissioners are allowed in a given governing body or context.
-
E.
numberOfAppointedMembers
Indicates the specific count of members who have been formally appointed to a group, body, or position.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5018176d481909536f50689f878d2 |
completed | April 19, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:35 a.m.