Triple

T15689443
Position Surface form Disambiguated ID Type / Status
Subject George Valentin E380286 entity
Predicate professionStatusLater P19158 FINISHED
Object unemployed actor 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: unemployed actor | Statement: [George Valentin, professionStatusLater, unemployed actor]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: professionStatusLater
Context triple: [George Valentin, professionStatusLater, unemployed actor]
  • A. memberLaterOccupation
    Indicates that an individual later held a particular occupation or position after an earlier point in time or role.
  • B. careerStatus
    Indicates the current stage, position, or condition of an entity within its professional or occupational life.
  • C. laterCareer chosen
    Indicates that the associated information or events pertain to a later stage or phase in an entity’s professional life or career trajectory.
  • D. professionalTitleAfterCompletion
    Indicates that an entity is granted or holds a specific professional title as a result of successfully completing a particular program, course, or qualification.
  • E. hasProfessionalStatus
    Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
  • 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_69d86d99e860819094b6957cde470f2c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f4e59988190aaf12f6a07c8f0e4 completed April 16, 2026, 2:54 a.m.
PD Predicate disambiguation batch_69deda8c856c8190882330114f9a1a5f completed April 15, 2026, 12:23 a.m.
Created at: April 10, 2026, 4:44 a.m.