Triple

T18263828
Position Surface form Disambiguated ID Type / Status
Subject Mr. Lewisham E437431 entity
Predicate appearsIn P795 FINISHED
Object Love and Mr. Lewisham 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: Love and Mr. Lewisham | Statement: [Mr. Lewisham, appearsIn, Love and Mr. Lewisham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Love and Mr. Lewisham
Context triple: [Mr. Lewisham, appearsIn, Love and Mr. Lewisham]
  • A. Love and Mr. Lewisham chosen
    Love and Mr. Lewisham is an early novel by H. G. Wells that explores the romantic and social struggles of a young, idealistic schoolteacher in late Victorian England.
  • B. Miracle in Soho
    Miracle in Soho is a 1957 British romantic drama film set in London’s Soho district, noted for its depiction of immigrant life and directed by Ken Annakin.
  • C. Sir John in Love
    Sir John in Love is a four-act opera by Ralph Vaughan Williams, based on Shakespeare’s "The Merry Wives of Windsor" and noted for its rich use of English folk melodies.
  • D. The Loved One
    The Loved One is a darkly comic novella by Evelyn Waugh that satirizes the American funeral industry and Hollywood culture.
  • E. The Loved One
    The Loved One is a 1965 satirical black comedy film, based on Evelyn Waugh’s novel, that skewers the American funeral industry and Hollywood culture.
  • 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_69d8b913351c8190932b6a426de04b41 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ff78b188819081da8e1d389c6c79 completed April 19, 2026, 4:14 p.m.
Created at: April 10, 2026, 10:34 a.m.