Triple
T45124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Senate |
E886
|
entity |
| Predicate | hasMembersPerState |
P2838
|
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: [United States Senate, hasMembersPerState, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMembersPerState Context triple: [United States Senate, hasMembersPerState, 2]
-
A.
numberOfMemberStates
Indicates the total count of member states associated with a given entity or organization.
-
B.
hasNumberOfMemberInstitutions
Indicates the quantitative count of member institutions associated with a given entity.
-
C.
numberOfMemberStateMissions
Indicates the total count of missions associated with or undertaken by the member states in a given context.
-
D.
numberOfStates
Indicates the total count of distinct states or conditions associated with an entity or system.
-
E.
isCharterMemberOf
Indicates that an entity is an original or founding member of a group, organization, or institution at the time it was established.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24ba7016481909d595402712db6e2 |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24abbd32c81908cec461d9097662e |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24ba5da048190a484963cb5a9bb2b |
completed | Feb. 28, 2026, 1:57 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.