Triple
T26778802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Article II: Obstruction of Congress |
E670192
|
entity |
| Predicate | impeachmentNumber |
P10903
|
FINISHED |
| Object | first impeachment of Donald Trump |
—
|
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: first impeachment of Donald Trump | Statement: [Article II: Obstruction of Congress, impeachmentNumber, first impeachment of Donald Trump]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impeachmentNumber Context triple: [Article II: Obstruction of Congress, impeachmentNumber, first impeachment of Donald Trump]
-
A.
impeachmentYear
Indicates the year in which an entity (typically a public official) was formally impeached.
-
B.
impeachmentInitiation
Indicates the formal start of a process to charge and potentially remove a public official from office for alleged misconduct.
-
C.
numberOfArticlesOfImpeachment
chosen
Indicates the specific count of formal impeachment charges brought against a person or officeholder.
-
D.
impeachmentTarget
Indicates that an entity is the person or official against whom impeachment proceedings are directed.
-
E.
impeachmentOutcome
Indicates the result or final status of an impeachment process against a specific 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6197855f481909d48a0fe694b8c53 |
completed | May 2, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 4:07 a.m.