Triple
T21763293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max-3-SAT |
E537214
|
entity |
| Predicate | hasAlternativeObjectiveFunction |
P116644
|
FINISHED |
| Object | fraction of satisfied clauses |
—
|
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: fraction of satisfied clauses | Statement: [Max-3-SAT, hasAlternativeObjectiveFunction, fraction of satisfied clauses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternativeObjectiveFunction Context triple: [Max-3-SAT, hasAlternativeObjectiveFunction, fraction of satisfied clauses]
-
A.
objectiveFunctionType
chosen
Indicates the specific kind or category of objective function used to evaluate or optimize a system, model, or decision.
-
B.
hasAlternativeReferent
Indicates that an entity can also be referred to or identified by an alternative name, label, or reference.
-
C.
hasEquivalentFormulation
Indicates that two representations, statements, or formulations express the same underlying meaning, condition, or effect, even if they differ in form.
-
D.
hasAlternativeMultiplierChoice
Indicates that an entity is associated with one or more alternative options for a multiplier that can be chosen instead of a default value.
-
E.
hasAlternativeHypothesis
Indicates that an entity is associated with another entity that serves as a different or competing hypothesis to explain the same phenomenon or data.
- 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_69e0c46f5d1c8190bf830409e98464e5 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f031a711dc8190a786c9849dc344e8 |
completed | April 28, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69e6be6299988190a34c98fa76d94700 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:51 p.m.