Triple
T101031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1932 United States presidential election |
E2039
|
entity |
| Predicate | typeOfVictory |
P6374
|
FINISHED |
| Object | landslide |
—
|
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: landslide | Statement: [1932 United States presidential election, typeOfVictory, landslide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfVictory Context triple: [1932 United States presidential election, typeOfVictory, landslide]
-
A.
victoryIn
Indicates that one entity achieves a win or success in a specific contest, event, or competitive context involving another entity.
-
B.
winningTeam
Indicates which team is the victor in a given competition, game, or contest.
-
C.
prizeType
Indicates the specific category or kind of prize associated with an entity or event.
-
D.
typeOfDefense
Indicates the specific kind or category of defense employed or possessed in a given context.
-
E.
revolutionVictoryYear
Indicates the year in which a revolution achieved victory or successfully overthrew the existing regime.
- 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.