Triple

T37224992
Position Surface form Disambiguated ID Type / Status
Subject The Cat That Hated People E922981 entity
Predicate featuresContrast P199229 FINISHED
Object Earthly annoyances versus bizarre lunar annoyances 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: Earthly annoyances versus bizarre lunar annoyances | Statement: [The Cat That Hated People, featuresContrast, Earthly annoyances versus bizarre lunar annoyances]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: featuresContrast
Context triple: [The Cat That Hated People, featuresContrast, Earthly annoyances versus bizarre lunar annoyances]
  • A. achievesContrast
    Indicates that one entity creates or enhances a visual or conceptual difference relative to another entity.
  • B. featuresLoudQuietContrast
    Indicates a relationship where something is characterized by a strong contrast between loud and quiet elements.
  • C. providesContrastWith
    Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
  • D. includesContrast chosen
    Indicates that one element contains or incorporates a comparison highlighting differences between two or more entities or ideas.
  • E. textureContrast
    Indicates a relationship where two surfaces or regions differ noticeably in their tactile or visual texture qualities.
  • 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_69f76ea7f0008190b31b8e30f3d05a71 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_6a037c8efcd4819088c2aeead65d93df completed May 12, 2026, 7:16 p.m.
PD Predicate disambiguation batch_6a037a11efc08190bb7cacc1325b4dc6 completed May 12, 2026, 7:05 p.m.
Created at: May 3, 2026, 4:15 p.m.