Triple
T17139738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | second impeachment of Donald Trump |
E415931
|
entity |
| Predicate | senateVoteNotGuilty |
P10904
|
FINISHED |
| Object | 43 |
—
|
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: 43 | Statement: [second impeachment of Donald Trump, senateVoteNotGuilty, 43]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: senateVoteNotGuilty Context triple: [second impeachment of Donald Trump, senateVoteNotGuilty, 43]
-
A.
acquittedOf
Indicates that an authority has formally cleared an entity of a specific charge, accusation, or wrongdoing.
-
B.
acquittedBy
Indicates that an entity was formally cleared of charges or blame through a decision or judgment made by another entity.
-
C.
numberOfAcquittals
Indicates the count of instances in which an entity has been formally acquitted of charges or accusations.
-
D.
marginOfAcquittalOnKeyArticles
chosen
Indicates the numerical difference between votes for and against acquittal on the principal or most important charges in a case.
-
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.