Triple
T26079366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Senate from Rhode Island |
E657787
|
entity |
| Predicate | numberOfVotesInSenate |
P25770
|
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 from Rhode Island, numberOfVotesInSenate, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfVotesInSenate Context triple: [United States Senate from Rhode Island, numberOfVotesInSenate, 2]
-
A.
numberOfSenates
Indicates the total count of senate bodies associated with or present in a given context or entity.
-
B.
numberOfSeatsInSenate
Indicates the total count of seats allocated in a given senate.
-
C.
numberOfSenators
Indicates the total count of senators associated with a given political body, region, or entity.
-
D.
numberOfSupportVotesInChamber
Indicates the count of votes cast in favor of a proposal within a specific legislative chamber.
-
E.
senateVoteTallyFor
chosen
Indicates the recorded vote count or outcome in the senate for a particular measure, motion, or item.
- 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_69ee5bbf0d208190801ee95d4f07fb16 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69fd5d48855c8190bd93070b6a00d8b5 |
completed | May 8, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69fd5c9aabb88190912800d90184a89d |
completed | May 8, 2026, 3:46 a.m. |
Created at: April 26, 2026, 7:36 p.m.