Triple

T21402865
Position Surface form Disambiguated ID Type / Status
Subject Robert Stevenson E527954 entity
Predicate directed P7373 FINISHED
Object The Love Bug 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: The Love Bug | Statement: [Robert Stevenson, directed, The Love Bug]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Love Bug
Context triple: [Robert Stevenson, directed, The Love Bug]
  • A. Love Bug
    Love Bug is a notorious computer worm from 2000 that spread rapidly via email by masquerading as a love letter and causing widespread damage to systems worldwide.
  • B. The Love Bug (1968 film) chosen
    The Love Bug (1968 film) is a Disney live-action comedy about a sentient Volkswagen Beetle named Herbie that becomes a racing champion and launched the popular Herbie film franchise.
  • C. The Grouchy Ladybug
    The Grouchy Ladybug is a popular children's picture book by Eric Carle that follows a bad-tempered ladybug learning about manners and sharing over the course of a day.
  • D. The Big Bug
    The Big Bug is a film featuring Chinese actor Peng Yuchang in a prominent role.
  • E. Ladybugs
    Ladybugs is a 1992 sports comedy film in which Jonathan Brandis plays a boy who disguises himself as a girl to help a struggling girls' soccer team.
  • 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_69e0b520ee3c8190abddbee7e37e834c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b171f3448190add844a426b0a606 completed April 22, 2026, 11:30 a.m.
Created at: April 16, 2026, 5:24 p.m.