Triple

T22395916
Position Surface form Disambiguated ID Type / Status
Subject Love and Monsters E553628 entity
Predicate screenwriter P2831 FINISHED
Object Matthew Robinson 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: Matthew Robinson | Statement: [Love and Monsters, screenwriter, Matthew Robinson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew Robinson
Context triple: [Love and Monsters, screenwriter, Matthew Robinson]
  • A. Matthew Robinson
    Matthew Robinson was an 18th-century English writer and politician, best known as the son of the prominent Bluestocking intellectual Elizabeth Montagu.
  • B. Matthew Robinson
    Matthew Robinson is a filmmaker and screenwriter best known for co-writing and co-directing the satirical comedy film "The Invention of Lying."
  • C. Matthew Robinson chosen
    Matthew Robinson is a screenwriter known for co-writing the live-action adventure comedy film "Dora and the Lost City of Gold."
  • D. Matthew Robinson
    Matthew Robinson is a British television director best known for his work on the long-running science fiction series Doctor Who.
  • E. Matt Robinson
    Matt Robinson was an American actor, writer, and producer best known for originating the role of Gordon on Sesame Street and for his work in children's television.
  • 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_69e11e4da7048190b4387d422a9a0de5 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1585e84b081908c95ed3e0d987ed8 completed April 29, 2026, 1:01 a.m.
Created at: April 16, 2026, 8:45 p.m.