Triple
T23849104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 United States Senate election in Florida |
E592106
|
entity |
| Predicate | campaignSpendingLevel |
P79663
|
FINISHED |
| Object | among highest of 2018 Senate races |
—
|
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: among highest of 2018 Senate races | Statement: [2018 United States Senate election in Florida, campaignSpendingLevel, among highest of 2018 Senate races]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campaignSpendingLevel Context triple: [2018 United States Senate election in Florida, campaignSpendingLevel, among highest of 2018 Senate races]
-
A.
budgetLevel
Indicates the relative amount of financial resources allocated or available for something, typically categorized by level (e.g., low, medium, high).
-
B.
spendSize
chosen
Indicates the amount or magnitude of spending associated with an entity or transaction.
-
C.
campaignScope
Indicates the extent or boundaries of influence, coverage, or activity associated with a particular campaign.
-
D.
commercialCostPer30SecondsUSD
Indicates the monetary cost, in U.S. dollars, to run a 30-second commercial.
-
E.
typeOfSpendingAffected
Indicates that a particular kind or category of spending is influenced, changed, or impacted by another factor or event.
- 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_69e25d221d908190b9b502ad31e66a3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c9862cb081908e2433678190dee8 |
completed | April 29, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:10 p.m.