Triple

T28047934
Position Surface form Disambiguated ID Type / Status
Subject Dr. Tyrone Berger E708732 entity
Predicate workRelationshipWith P20699 FINISHED
Object Conrad Jarrett NE NERFINISHED

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: Conrad Jarrett | Statement: [Dr. Tyrone Berger, workRelationshipWith, Conrad Jarrett]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: workRelationshipWith
Context triple: [Dr. Tyrone Berger, workRelationshipWith, Conrad Jarrett]
  • A. employerRelationship
    Indicates a relationship in which one entity acts as the employer of another, having authority to hire, direct, and compensate the other party for work performed.
  • B. basedOnWorkRelationship
    Indicates that one entity is derived from, adapted from, or otherwise created on the basis of another underlying work.
  • C. workRelatedTo chosen
    Indicates a relationship where one entity’s work, tasks, or professional activities are connected, associated, or relevant to those of another entity.
  • D. worksInCloseRelationshipWith
    Indicates a collaborative professional relationship in which two or more entities work together closely and interact frequently to achieve shared goals.
  • E. workTitleRelation
    Indicates a relationship where one entity is the title or name of a work (such as a book, film, or artwork) associated with 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_69ef9b6df9f48190bbb971d02cbe1b65 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f63f3559148190bca6f6c3e45d3961 completed May 2, 2026, 6:15 p.m.
PD Predicate disambiguation batch_69f63710d17c819084cfe96e6df334fd completed May 2, 2026, 5:40 p.m.
Created at: April 27, 2026, 8:31 p.m.