Triple

T7906296
Position Surface form Disambiguated ID Type / Status
Subject Helen Sharp E183584 entity
Predicate hasLoveInterest P7325 FINISHED
Object Ernest Menville E183585 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: Ernest Menville | Statement: [Helen Sharp, hasLoveInterest, Ernest Menville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ernest Menville
Context triple: [Helen Sharp, hasLoveInterest, Ernest Menville]
  • A. Ernest Menville chosen
    Ernest Menville is a beleaguered plastic surgeon and mortician caught between two vain, immortal rivals in the dark comedy film "Death Becomes Her."
  • B. John Norville
    John Norville is a screenwriter best known for co-writing the story for Disney's adventure film "Jungle Cruise."
  • C. Donald Oenslager
    Donald Oenslager was an influential American theatrical set designer and educator known for helping shape modern stage design on Broadway in the mid-20th century.
  • D. Douglass Dumbrille
    Douglass Dumbrille was a Canadian-born character actor best known for his prolific work in Hollywood films of the 1930s and 1940s, often portraying suave villains and authority figures.
  • E. Carl Esmond
    Carl Esmond was an Austrian-born American actor known for his character roles in Hollywood films from the 1930s through the 1960s.
  • 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_69ca828dec0c81908b8f55a4dbbb53ff completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a5871b8819087ad69c116c40091 completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5bc9dfa88190aa5261bdf44823ab completed March 31, 2026, 5:29 a.m.
Created at: March 30, 2026, 5:03 p.m.