Triple
T6999009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California State Lottery |
E162286
|
entity |
| Predicate | profitAllocation |
P65949
|
FINISHED |
| Object | prizes |
—
|
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: prizes | Statement: [California State Lottery, profitAllocation, prizes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: profitAllocation Context triple: [California State Lottery, profitAllocation, prizes]
-
A.
allocation
chosen
Indicates the distribution or assignment of resources, responsibilities, or items among entities according to some rule or plan.
-
B.
profitsFrom
Indicates that one entity gains financial or material benefit as a result of another entity’s actions, existence, or situation.
-
C.
allocationShare
Indicates the proportion or portion of a total resource, amount, or benefit that is assigned to a particular entity within an allocation.
-
D.
parallelDivision
Indicates that one entity is divided or partitioned in a way that runs parallel to the division or partitioning of another entity.
-
E.
allocatesAccordingTo
Indicates that one entity distributes or assigns resources, tasks, or responsibilities to others based on a specified rule, criterion, or plan.
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbf083b481909dd30e28e908dfdf |
completed | March 27, 2026, 7:35 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c67c94819084fdcf0398606027 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:33 p.m.