Triple
T893162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew Johnson |
E19284
|
entity |
| Predicate | wasImpeached |
P2514
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Andrew Johnson, wasImpeached, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasImpeached Context triple: [Andrew Johnson, wasImpeached, yes]
-
A.
impeached
chosen
Indicates that a formal charge of misconduct has been brought against a public official through an official legislative or judicial process.
-
B.
canImpeach
Indicates that one entity has the authority or power to formally impeach another entity.
-
C.
impeachmentYear
Indicates the year in which an entity (typically a public official) was formally impeached.
-
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.
numberOfArticlesOfImpeachment
Indicates the specific count of formal impeachment charges brought against a person or officeholder.
- 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_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad212cd8819091eb1b7d606f5afd |
completed | March 1, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69a4aa9372e88190b5a9db4afdc045c6 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.