Triple

T14552429
Position Surface form Disambiguated ID Type / Status
Subject June Osborne E341450 entity
Predicate associatedWith P37 FINISHED
Object Serena Joy Waterford E474445 NE 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: Serena Joy Waterford | Statement: [June Osborne, associatedWith, Serena Joy Waterford]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Serena Joy Waterford
Context triple: [June Osborne, associatedWith, Serena Joy Waterford]
  • A. Serena Joy Waterford chosen
    Serena Joy Waterford is the strict, embittered Wife of a high-ranking Commander in Margaret Atwood’s "The Handmaid’s Tale," known for her complicity in and enforcement of Gilead’s oppressive regime.
  • B. Serena Brown
    Serena Brown is the daughter of Bob Brown.
  • C. Serena Evans
    Serena Evans is a British actress best known for her role in the BBC sitcom "The Thin Blue Line."
  • D. Serena
    Serena is a central character in George Gershwin's opera "Porgy and Bess," known as a strong, devout woman who provides emotional and moral support within the Catfish Row community.
  • E. Serena
    "Serena" is a 2014 period drama film directed by Susanne Bier, starring Jennifer Lawrence and Bradley Cooper as a married couple whose timber empire unravels in Depression-era North Carolina.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb2ee34208190bf040a513767c958 completed April 14, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ab7d698819085fd81d7b6f96317 completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:23 a.m.