Triple

T37577561
Position Surface form Disambiguated ID Type / Status
Subject Dante Hicks E934865 entity
Predicate workplaceRelationship P20699 FINISHED
Object co-worker of Randal Graves 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: co-worker of Randal Graves | Statement: [Dante Hicks, workplaceRelationship, co-worker of Randal Graves]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: workplaceRelationship
Context triple: [Dante Hicks, workplaceRelationship, co-worker of Randal Graves]
  • A. basedOnWorkRelationship
    Indicates that one entity is derived from, adapted from, or otherwise created on the basis of another underlying work.
  • B. 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.
  • 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. hasRelationshipToWork
    Indicates a relationship where an entity has a specific connection, role, or association with a particular work or piece of work.
  • E. hasFamilyRelationInWork
    Indicates that there exists a family relationship between two entities within the context of a specific work (e.g., book, film, or other creative work).
  • 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_69f76ecd99148190be327e391a70f5b6 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba61dff5081909fec88a7aeb0c8a1 completed May 6, 2026, 8:35 p.m.
PD Predicate disambiguation batch_69fba350e9a8819095893229d9643572 completed May 6, 2026, 8:23 p.m.
Created at: May 3, 2026, 4:17 p.m.