Triple
T29054061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abraham Lincoln’s Ten Percent Plan |
E735340
|
entity |
| Predicate | loyaltyThreshold |
P158299
|
FINISHED |
| Object | 10 percent of 1860 voters |
—
|
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: 10 percent of 1860 voters | Statement: [Abraham Lincoln’s Ten Percent Plan, loyaltyThreshold, 10 percent of 1860 voters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loyaltyThreshold Context triple: [Abraham Lincoln’s Ten Percent Plan, loyaltyThreshold, 10 percent of 1860 voters]
-
A.
loyaltyGoal
Indicates that one entity has the objective or commitment to remain faithful, supportive, or devoted to another entity or cause.
-
B.
loyaltyAtStart
chosen
Indicates that a specified level or state of loyalty is present at the beginning of a defined period, event, or interaction.
-
C.
loyaltySymbolizedBy
Indicates that an instance of loyalty is represented or expressed by a particular symbol or emblem.
-
D.
loyaltyProgramTierDependent
Indicates that the applicability, behavior, or outcome of something depends on a customer's current tier or level within a loyalty program.
-
E.
loyaltyIncentive
Indicates a relationship where benefits or rewards are provided to encourage or recognize continued commitment or repeat engagement.
- 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_69f077e64b88819094d37bdbca8191b3 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6609061508190ae12005d993e42bc |
completed | May 2, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 10:10 a.m.