Triple

T3599684
Position Surface form Disambiguated ID Type / Status
Subject Resch Center E76224 entity
Predicate namesakeRole P12885 FINISHED
Object former CEO of KI Industries 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: former CEO of KI Industries | Statement: [Resch Center, namesakeRole, former CEO of KI Industries]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: namesakeRole
Context triple: [Resch Center, namesakeRole, former CEO of KI Industries]
  • A. namesakeDescription
    Indicates that the object provides a descriptive explanation of why or how the subject is considered a namesake of something or someone.
  • B. namesakeFullName
    Indicates that one entity’s full name is used as the namesake or source of the name for another entity.
  • C. namedPersonRole chosen
    Indicates that a person is identified by name as holding a specific role or position in a given context.
  • D. namesakeOccupation
    Indicates that one entity’s occupation is the same as, or derived from, the occupation associated with the other entity’s namesake.
  • E. nicknameForRole
    Indicates that one entity is an informal or alternative name commonly used to refer to a particular role or position represented by another entity.
  • 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_69ad85d93dcc819094fba90cf70f4996 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc19fd57481908ce5c9daf168e213 completed March 8, 2026, 6:36 p.m.
PD Predicate disambiguation batch_69adb83b66708190bb9d2f23d6fd308e completed March 8, 2026, 5:56 p.m.
Created at: March 8, 2026, 3:22 p.m.