Triple
T16763075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California Proposition 64 |
E407392
|
entity |
| Predicate | earmarksRevenueFor |
P85702
|
FINISHED |
| Object | youth programs |
—
|
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: youth programs | Statement: [California Proposition 64, earmarksRevenueFor, youth programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earmarksRevenueFor Context triple: [California Proposition 64, earmarksRevenueFor, youth programs]
-
A.
revenue
Indicates the amount of income generated by an entity from its business activities or operations over a specified period.
-
B.
isEarmarked
chosen
Indicates that something has been specifically designated, reserved, or set aside for a particular purpose, use, or recipient.
-
C.
revenueSources
Indicates the relationship identifying where an entity’s revenue comes from or the different streams that generate its income.
-
D.
revenueLevel
Indicates the relative amount or tier of revenue associated with an entity or activity.
-
E.
revenueUse
Indicates how generated revenue is allocated, spent, or applied toward specific purposes or activities.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3abee862c819086d9bf01e623a8ce |
completed | April 18, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69e319cbd79c8190a03587a61c18bec0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:21 a.m.