Triple

T22716325
Position Surface form Disambiguated ID Type / Status
Subject Anger Management (TV series) E561740 entity
Predicate mainCharacterSpecialization P149420 FINISHED
Object anger management therapy 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: anger management therapy | Statement: [Anger Management (TV series), mainCharacterSpecialization, anger management therapy]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mainCharacterSpecialization
Context triple: [Anger Management (TV series), mainCharacterSpecialization, anger management therapy]
  • A. characterSelection
    Indicates the relationship where a user or system chooses one or more characters from a set of available options.
  • B. creatorSpecialization
    Indicates the specific field, discipline, or area of expertise in which a creator primarily works or is specialized.
  • C. hasFictionalSpecialization
    Indicates that an entity’s area of focus, expertise, or role is within a fictional or imaginative domain rather than a real-world specialization.
  • D. mainMortalCharacter
    Indicates that the referenced entity serves as the primary mortal (non-immortal) character in the context of a story or narrative.
  • E. heroClass
    Indicates the character class or role that a hero belongs to within a given system or context.
  • 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_69e2454fc984819088213b58ee87a002 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1790e14c88190af6acb27910ae9c1 completed April 29, 2026, 3:20 a.m.
PD Predicate disambiguation batch_69ee62bd657c81909f7b01245b080a5f completed April 26, 2026, 7:08 p.m.
PDg Predicate description generation batch_69ee8843d3308190b6e22bb98ae5c3d8 completed April 26, 2026, 9:48 p.m.
Created at: April 17, 2026, 3:19 p.m.