Triple

T35858123
Position Surface form Disambiguated ID Type / Status
Subject Helga E1036562 entity
Predicate isOppositeInMeaningTo P21665 FINISHED
Object profane 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: profane | Statement: [Helga, isOppositeInMeaningTo, profane]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: isOppositeInMeaningTo
Context triple: [Helga, isOppositeInMeaningTo, profane]
  • A. opposite
    Indicates that one entity is positioned or oriented directly across from, or in a contrary or reverse relation to, 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. hasOppositeConnotationInModernUsage
    Indicates that one concept or expression now carries a meaning or emotional tone in contemporary usage that is opposite to that of another.
  • D. isOppositionCounterpartOf
    Indicates a relationship where one entity serves as the opposing or counterpart force, side, or position to another within a conflict, competition, or contrast.
  • E. counterpartRelation
    Indicates a reciprocal relationship where two entities serve as corresponding or equivalent counterparts to each other in a given context.
  • 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_69f76e1b4aa481909630373171eb5ec6 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa3883d48190b05e3d2da7a017ae completed May 3, 2026, 8:04 p.m.
PD Predicate disambiguation batch_69f7a8d435288190b30b1991fb003121 completed May 3, 2026, 7:58 p.m.
Created at: May 3, 2026, 4:06 p.m.