Triple

T9885154
Position Surface form Disambiguated ID Type / Status
Subject Neville Sinclair E180911 entity
Predicate associatedWith P37 FINISHED
Object Jenny Blake E690124 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: Jenny Blake | Statement: [Neville Sinclair, associatedWith, Jenny Blake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jenny Blake
Context triple: [Neville Sinclair, associatedWith, Jenny Blake]
  • A. Jenny Blake chosen
    Jenny Blake is the courageous and resourceful love interest of stunt pilot Cliff Secord in the 1991 adventure film "The Rocketeer."
  • B. Jenny Morrison
    Jenny Morrison is an Australian woman best known as the wife of former Prime Minister Scott Morrison and for her public role during his time in office.
  • C. Jenny Hill
    Jenny Hill is a character in the fantasy drama film "Big Fish," appearing as one of the many figures woven into Edward Bloom’s larger-than-life storytelling.
  • D. Jenny Robertson
    Jenny Robertson is an American actress known for her work in film and television, including roles in comedies and dramas since the 1980s.
  • E. Jenny Mullion
    Jenny Mullion is a minor character in Aldous Huxley’s satirical novel "Crome Yellow," appearing among the eclectic guests at the country-house gathering that the book portrays.
  • 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_69ca828082cc8190a40f8d299caa6545 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cdb45549488190833200977d558e47 completed April 2, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23d15df30819092ae896786564478 completed April 5, 2026, 10:44 a.m.
Created at: March 30, 2026, 8:38 p.m.