Triple

T36879241
Position Surface form Disambiguated ID Type / Status
Subject Luke Bankole E911427 entity
Predicate hasRelationshipTypeWith June Osborne P205096 FINISHED
Object romantic relationship 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: romantic relationship | Statement: [Luke Bankole, hasRelationshipTypeWith June Osborne, romantic relationship]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWith June Osborne
Context triple: [Luke Bankole, hasRelationshipTypeWith June Osborne, romantic relationship]
  • A. hasRelationshipTypeWith Owen Hunt
    Indicates that there exists a specific type of interpersonal or relational connection between an entity and Owen Hunt.
  • B. hasRelationshipTypeWith Tai Frasier
    Indicates that there exists a specific type of relationship between an entity and Tai Frasier.
  • C. hasRelationshipTypeWithRoryGilmore
    Indicates that an entity has a specific type of interpersonal relationship or connection with Rory Gilmore.
  • D. relationshipTypeWithLorelai
    Indicates the specific nature or category of relationship that an entity has with Lorelai.
  • E. hasRelationshipTypeWith Anastasia Steele
    Indicates that an entity has a specific type of relationship or relational role with Anastasia Steele.
  • 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_69f76e82339881909607a65c0503d941 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_6a037cad051c8190b28b354b89208574 completed May 12, 2026, 7:17 p.m.
PD Predicate disambiguation batch_6a037a0e039481908a4a2666f76c5363 completed May 12, 2026, 7:05 p.m.
PDg Predicate description generation batch_6a037c82f8c88190bd77a086023ac0e1 completed May 12, 2026, 7:16 p.m.
Created at: May 3, 2026, 4:13 p.m.