Triple

T38570068
Position Surface form Disambiguated ID Type / Status
Subject Cleaver E929239 entity
Predicate containsCharacterParallel P132767 FINISHED
Object boss character modeled on Tony Soprano 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: boss character modeled on Tony Soprano | Statement: [Cleaver, containsCharacterParallel, boss character modeled on Tony Soprano]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: containsCharacterParallel
Context triple: [Cleaver, containsCharacterParallel, boss character modeled on Tony Soprano]
  • A. containsCharacter
    Indicates that one entity includes a specific character as part of its content or composition.
  • B. containsCharacterAction
    Indicates that an entity includes or features an action performed by a character within it.
  • C. parallelCharacter chosen
    Indicates that one character corresponds to or mirrors another character in a parallel role, function, or narrative pattern.
  • D. hasRecurringCharacterFrom
    Indicates that one work or series includes a character who also appears recurrently in another work or series.
  • E. hasCharacterSequence
    Indicates that one entity contains, exhibits, or follows a specific ordered sequence of characters.
  • 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_69f76ebd2248819083978362d81fa35e completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_6a0227ce59a081909fe1ba1181d86b4d completed May 11, 2026, 7:02 p.m.
PD Predicate disambiguation batch_6a02273989208190beb948b8c7bdaee3 completed May 11, 2026, 7 p.m.
Created at: May 3, 2026, 4:32 p.m.