Triple
T29054069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abraham Lincoln’s Ten Percent Plan |
E735340
|
entity |
| Predicate | leniencyLevel |
P165964
|
FINISHED |
| Object | lenient toward former Confederates |
—
|
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: lenient toward former Confederates | Statement: [Abraham Lincoln’s Ten Percent Plan, leniencyLevel, lenient toward former Confederates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leniencyLevel Context triple: [Abraham Lincoln’s Ten Percent Plan, leniencyLevel, lenient toward former Confederates]
-
A.
hasLeniencyProgram
Indicates that an entity offers or participates in a formal leniency program, typically reducing penalties or sanctions under specified conditions.
-
B.
politenessLevel
Indicates the degree of courteousness or respectfulness expressed by one entity toward another in an interaction.
-
C.
restrictionLevel
Indicates the degree or strictness of limitations or constraints imposed on an entity, action, or access.
-
D.
enforcementStrength
Indicates the degree or intensity with which rules, laws, or policies are applied and enforced in a given context.
-
E.
sanctioningLevel
Indicates the degree or severity of formal penalties, restrictions, or disciplinary measures imposed in response to a violation or noncompliant behavior.
- 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_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. |
| PDg | Predicate description generation | batch_69f65ad638ac8190a17bb987fce53279 |
completed | May 2, 2026, 8:13 p.m. |
Created at: April 28, 2026, 10:10 a.m.