Triple
T24793024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Mafia Is Not an Equal Opportunity Employer |
E620301
|
entity |
| Predicate | titleCharacterization |
P158727
|
FINISHED |
| Object | critical of Mafia practices |
—
|
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: critical of Mafia practices | Statement: [The Mafia Is Not an Equal Opportunity Employer, titleCharacterization, critical of Mafia practices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleCharacterization Context triple: [The Mafia Is Not an Equal Opportunity Employer, titleCharacterization, critical of Mafia practices]
-
A.
theoryCharacterization
Indicates that one entity provides a defining description, formulation, or account of a theory associated with another entity.
-
B.
scopeCharacterization
Indicates how the extent, boundaries, or coverage of something is defined, described, or qualified in relation to another entity or context.
-
C.
sourceCharacterization
Indicates that one entity describes, explains, or characterizes the origin, provenance, or source of another entity.
-
D.
studyCharacterization
Indicates a relationship where an entity conducts a detailed examination or analysis to characterize or define the properties, behavior, or features of another entity.
-
E.
resultCharacterization
Indicates how the outcome of an event, process, or action is qualitatively described or characterized.
- 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_69e2fabe77c8819085f7ce6486248139 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f48b9b687881908fd87a2f5fa0b1e7 |
completed | May 1, 2026, 11:16 a.m. |
| PD | Predicate disambiguation | batch_69f48060597c8190a4414e4e4fcb1fec |
completed | May 1, 2026, 10:28 a.m. |
| PDg | Predicate description generation | batch_69f48b9058d081908ec9af261ee092e2 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 18, 2026, 4:47 a.m.