Triple

T28518763
Position Surface form Disambiguated ID Type / Status
Subject ka-tet E721697 entity
Predicate hasOppositeOrContrast P21665 FINISHED
Object random or unconnected group 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: random or unconnected group | Statement: [ka-tet, hasOppositeOrContrast, random or unconnected group]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasOppositeOrContrast
Context triple: [ka-tet, hasOppositeOrContrast, random or unconnected group]
  • A. providesContrastWith
    Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
  • B. hasConceptualOpposite chosen
    Indicates that one entity represents a concept that is fundamentally opposed or contrary in meaning to the concept represented by another entity.
  • C. hasContrastingRelationshipWith
    Indicates a relationship in which two entities are opposed, divergent, or markedly different in qualities, roles, or effects.
  • D. oftenContrastedWith
    Indicates that one entity is frequently compared to another in a way that highlights their differences or opposing characteristics.
  • E. hasOppositionalElements
    Indicates that something contains components or aspects that are in conflict, contrast, or opposition to each other.
  • 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_69f01a5cbcc4819083fb4e723378713e completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f6e6029a10819098ff21f58079e70e completed May 3, 2026, 6:06 a.m.
PD Predicate disambiguation batch_69f6e3d5e8188190b1e1c2e5d1b77031 completed May 3, 2026, 5:57 a.m.
Created at: April 28, 2026, 3:19 a.m.