Triple

T35000533
Position Surface form Disambiguated ID Type / Status
Subject Chance Wayne E1009661 entity
Predicate relationshipTypeWith Heavenly Finley P206793 FINISHED
Object tragic romance 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: tragic romance | Statement: [Chance Wayne, relationshipTypeWith Heavenly Finley, tragic romance]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Heavenly Finley
Context triple: [Chance Wayne, relationshipTypeWith Heavenly Finley, tragic romance]
  • A. hasRelationshipTypeWith Fran Fine
    Indicates that an entity is connected to Fran Fine by a specific, categorized type of relationship (e.g., familial, professional, romantic, or social).
  • B. inRelationshipWith
    Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
  • C. relationshipTypeWith Francesca Johnson
    Indicates the specific nature or category of the relationship that an entity has with Francesca Johnson.
  • D. hasRelationshipTypeWith Tai Frasier
    Indicates that there exists a specific type of relationship between an entity and Tai Frasier.
  • E. haveRelationshipWith
    Indicates that one entity is in some form of defined relationship or association with another entity.
  • 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_69f76dcb716881909f75e4fd60ab2284 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_6a037c92f03c8190ae2751270b195423 completed May 12, 2026, 7:16 p.m.
PD Predicate disambiguation batch_6a0379ff1ba081908eda86acefcf69fb completed May 12, 2026, 7:05 p.m.
PDg Predicate description generation batch_6a037c82179081908325a59b8539b3a8 completed May 12, 2026, 7:16 p.m.
Created at: May 3, 2026, 4:01 p.m.