Triple
T17139737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | second impeachment of Donald Trump |
E415931
|
entity |
| Predicate | senateVoteGuilty |
P2842
|
FINISHED |
| Object | 57 |
—
|
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: 57 | Statement: [second impeachment of Donald Trump, senateVoteGuilty, 57]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: senateVoteGuilty Context triple: [second impeachment of Donald Trump, senateVoteGuilty, 57]
-
A.
impeachmentOutcome
Indicates the result or final status of an impeachment process against a specific officeholder.
-
B.
convictedBy
Indicates that an authority, typically a court or judge, has formally found an entity guilty of a crime or offense.
-
C.
impeachmentConvictionThreshold
chosen
Indicates the required level of support or number of votes needed to convict an official in an impeachment proceeding.
-
D.
impeachmentGrounds
Indicates that a particular reason, action, or circumstance serves as a valid basis or justification for initiating impeachment proceedings against an officeholder.
-
E.
notableRepublicanVotingToConvictOnArticleI
Indicates that the subject is a prominent Republican who voted to convict on the first article (Article I) of an impeachment.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f2d318a88190aae8d776376c8053 |
completed | April 18, 2026, 9:08 p.m. |
| PD | Predicate disambiguation | batch_69e3830192ac819091344a9e5a36c8c9 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:36 a.m.