Triple
T71815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California term limits law |
E1436
|
entity |
| Predicate | secondaryGoal |
P3579
|
FINISHED |
| Object | reduce career incumbency |
—
|
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: reduce career incumbency | Statement: [California term limits law, secondaryGoal, reduce career incumbency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryGoal Context triple: [California term limits law, secondaryGoal, reduce career incumbency]
-
A.
secondaryFunction
Indicates that an entity has an additional, supporting role or purpose beyond its primary function.
-
B.
hasPrimaryGoal
Indicates that an entity’s main or most important objective is the specified goal.
-
C.
primaryTarget
Indicates that an entity is the main or most important target of another entity’s action, focus, or effect.
-
D.
secondaryDomain
Indicates that one domain functions as a secondary or auxiliary domain in relation to a primary domain.
-
E.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f6997c081908b202f937eb2b14f |
completed | Feb. 28, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69a24eab7f408190a8275cb82474f575 |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a24f65170c8190bc541c8351456a4d |
completed | Feb. 28, 2026, 2:13 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.