Triple
T101033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1932 United States presidential election |
E2039
|
entity |
| Predicate | incumbentBlamedFor |
P6375
|
FINISHED |
| Object | economic crisis |
—
|
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: economic crisis | Statement: [1932 United States presidential election, incumbentBlamedFor, economic crisis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: incumbentBlamedFor Context triple: [1932 United States presidential election, incumbentBlamedFor, economic crisis]
-
A.
impeached
Indicates that a formal charge of misconduct has been brought against a public official through an official legislative or judicial process.
-
B.
defeatedCandidate
Indicates that one candidate has won an election or contest against another candidate, causing the other to lose.
-
C.
electedCandidate
Indicates that a particular person has been chosen as the winner in an election for a given position or office.
-
D.
canImpeach
Indicates that one entity has the authority or power to formally impeach another entity.
-
E.
hasIncumbentPresidentCandidate
Indicates that a political entity (such as a party, election, or race) has a current office-holding president running as a candidate in that contest.
- F. None of above. chosen
Provenance (4 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2563921f8819087f720b1c803579f |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2575d8a648190ad8e10d4b04e5e07 |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.