Triple

T8486071
Position Surface form Disambiguated ID Type / Status
Subject The Lady in the Van E200834 entity
Predicate cinematographyBy P1953 FINISHED
Object Andrew Dunn E89675 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: Andrew Dunn | Statement: [The Lady in the Van, cinematographyBy, Andrew Dunn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andrew Dunn
Context triple: [The Lady in the Van, cinematographyBy, Andrew Dunn]
  • A. Andrew Dunn chosen
    Andrew Dunn is a British cinematographer known for his work on numerous high-profile films and television productions.
  • B. Justin Dunn
    Justin Dunn is an American professional baseball pitcher who played college baseball at Boston College before being selected in the first round of the 2016 MLB Draft.
  • C. Kevin Dunn
    Kevin Dunn is an American character actor known for his supporting roles in numerous films and television series, including the romantic comedy-drama "Vicky Cristina Barcelona."
  • D. Eric Danchick
    Eric Danchick is a film producer known for his work on the movie "Bound 2."
  • E. Andrew Dillin
    Andrew Dillin is an American molecular biologist known for his influential research on the genetics of aging and protein homeostasis, particularly using C. elegans as a model organism.
  • 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_69ca831d7b148190a6e32c1de43ab13b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe53c4d608190a766c0e919a4b96f completed March 31, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6e8ea2748190b9ffa2f36c0e397c completed April 3, 2026, 7:38 a.m.
Created at: March 30, 2026, 6:12 p.m.