Triple

T31838769
Position Surface form Disambiguated ID Type / Status
Subject Olivier Mythodrama E812742 entity
Predicate approachCharacterizedBy P197172 FINISHED
Object use of classic plays as case studies 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: use of classic plays as case studies | Statement: [Olivier Mythodrama, approachCharacterizedBy, use of classic plays as case studies]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: approachCharacterizedBy
Context triple: [Olivier Mythodrama, approachCharacterizedBy, use of classic plays as case studies]
  • A. characterizedBy
    Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
  • B. findingCharacterization
    Indicates that a finding is being described or classified in terms of its nature, features, or diagnostic significance.
  • C. ruleCharacterization
    Indicates that one rule is described, defined, or characterized in terms of another rule or set of rules.
  • D. studyCharacterization
    Indicates a relationship where an entity conducts a detailed examination or analysis to characterize or define the properties, behavior, or features of another entity.
  • E. ownerCharacterization
    Indicates how an owner is characterized or described in relation to the entity they own.
  • 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_69f348ea7ffc8190a2ab43d80277cf59 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69fe7b1c506c8190869c1a22031e0571 completed May 9, 2026, 12:09 a.m.
PD Predicate disambiguation batch_69fe796b2bdc8190a86980d44008f875 completed May 9, 2026, 12:01 a.m.
PDg Predicate description generation batch_69fe7b1b3460819081172731b52ac15b completed May 9, 2026, 12:08 a.m.
Created at: April 30, 2026, 11:48 p.m.