Triple
T36757314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2024 United States federal elections |
E908085
|
entity |
| Predicate | occursEveryNumberOfYearsForPresidency |
P187103
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [2024 United States federal elections, occursEveryNumberOfYearsForPresidency, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occursEveryNumberOfYearsForPresidency Context triple: [2024 United States federal elections, occursEveryNumberOfYearsForPresidency, 4]
-
A.
inaugurationFrequency
Indicates how often inaugurations occur within a given time period or context.
-
B.
termCountAsPresident
Indicates the number of terms an individual has served in the role of president.
-
C.
numberOfTermInOffice
Indicates the specific ordinal count of how many terms an entity has served in a particular office or position.
-
D.
yearsInPower
Indicates the duration, typically in years, that an entity has held a position of authority or control.
-
E.
presidentialTerm
Indicates the period of time during which an individual officially serves as president of a country or organization.
- 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_69f76e779bec8190be0e1f87a131e0f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
| PDg | Predicate description generation | batch_69fb3424724c8190ba55ecf66fa0b171 |
completed | May 6, 2026, 12:29 p.m. |
Created at: May 3, 2026, 4:12 p.m.