Triple
T26778779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Article I: Abuse of Power |
E670191
|
entity |
| Predicate | senateYesVotesToConvict |
P2842
|
FINISHED |
| Object | 48 |
—
|
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: 48 | Statement: [Article I: Abuse of Power, senateYesVotesToConvict, 48]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: senateYesVotesToConvict Context triple: [Article I: Abuse of Power, senateYesVotesToConvict, 48]
-
A.
impeachmentConvictionThreshold
chosen
Indicates the required level of support or number of votes needed to convict an official in an impeachment proceeding.
-
B.
notableRepublicanVotingToConvictOnArticleI
Indicates that the subject is a prominent Republican who voted to convict on the first article (Article I) of an impeachment.
-
C.
numberOfRepublicanSenatorsVotingGuilty
Indicates the count of Republican senators who cast a "guilty" vote in a given vote or trial.
-
D.
subjectToImpeachmentVote
Indicates that a person or official is currently facing or has been formally brought to a legislative vote on whether to impeach them.
-
E.
numberOfStatesRequiredForRatification
Indicates the specific number of states that must approve or ratify a proposal for it to become valid or effective.
- 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f61fd623bc819091df736cf3419b99 |
completed | May 2, 2026, 4:01 p.m. |
| PD | Predicate disambiguation | batch_69f61b3d23f481908dfec27adace900a |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 4:07 a.m.