Triple
T5423054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1956 United States presidential election |
E121296
|
entity |
| Predicate | EisenhowerCarriedNumberOfStates |
P59237
|
FINISHED |
| Object | 41 |
—
|
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: 41 | Statement: [1956 United States presidential election, EisenhowerCarriedNumberOfStates, 41]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: EisenhowerCarriedNumberOfStates Context triple: [1956 United States presidential election, EisenhowerCarriedNumberOfStates, 41]
-
A.
numberOfStates
Indicates the total count of distinct states or conditions associated with an entity or system.
-
B.
number of states carried in 1936 election
Indicates the specific count of U.S. states that a candidate or party won in the 1936 election.
-
C.
numberOfStatesCarriedByRepublicanNominee
chosen
Indicates the number of U.S. states won or carried by the Republican presidential nominee in an election.
-
D.
numberOfGovernors
Indicates the total count of governors associated with or governing a specified entity.
-
E.
numberOfStatesRepresented
Indicates how many distinct states are represented or covered in a given context or entity.
- 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8812f84c819094d8516f69fff83d |
completed | March 20, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69bd8469f5e48190bbe5c8bdfe8925ea |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:06 p.m.