Triple

T22449613
Position Surface form Disambiguated ID Type / Status
Subject Sir Leoline E554954 entity
Predicate isDeceivedBy P7322 FINISHED
Object Geraldine NE NERFINISHED

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: Geraldine | Statement: [Sir Leoline, isDeceivedBy, Geraldine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geraldine
Context triple: [Sir Leoline, isDeceivedBy, Geraldine]
  • A. Geraldine chosen
    Geraldine is a feminine given name of Germanic origin that has been borne by various notable figures, including actress Geraldine Chaplin.
  • B. Geraldine
    Geraldine is a small rural service town in the South Island of New Zealand, known for its scenic surroundings and role as a gateway to the Canterbury high country.
  • C. Mary Clare
    Mary Clare was a British stage and film actress known for her character roles in early 20th-century cinema and theatre.
  • D. Gwendolyn
    Gwendolyn is a feminine given name most famously borne by the Pulitzer Prize–winning American poet Gwendolyn Brooks.
  • E. Ernestine
    Ernestine is the given first name of the American actress and sex symbol Jane Russell, known for her roles in classic Hollywood films of the 1940s and 1950s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e5113208190ab58c6b595f9d1d0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15b4ae8a08190ba6027f036ce62af completed April 29, 2026, 1:13 a.m.
Created at: April 16, 2026, 8:48 p.m.