Triple

T2137945
Position Surface form Disambiguated ID Type / Status
Subject The Lord of the Rings: The Two Towers E46697 entity
Predicate cinematographer P1953 FINISHED
Object Andrew Lesnie E102049 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 Lesnie | Statement: [The Lord of the Rings: The Two Towers, cinematographer, Andrew Lesnie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andrew Lesnie
Context triple: [The Lord of the Rings: The Two Towers, cinematographer, Andrew Lesnie]
  • A. Andrew Lesnie chosen
    Andrew Lesnie was an Australian cinematographer best known for his Oscar-winning work on Peter Jackson’s The Lord of the Rings film trilogy.
  • B. John Linson
    John Linson is an American film and television producer best known for creating the series Yellowstone and producing projects like Sons of Anarchy.
  • C. Greg Lansing
    Greg Lansing is an American college basketball coach best known for his tenure as head coach of the Indiana State Sycamores men's basketball program.
  • D. Michael Andrews
    Michael Andrews is an American film composer and musician known for his atmospheric scores for movies such as Donnie Darko and Bridesmaids.
  • E. Michael Ward
    Michael Ward was a British character actor known for his numerous supporting roles in mid-20th-century film and television comedies.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbe012aa481909ffa0a50e58efabb completed March 7, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae893ade888190980001116e10c874 completed March 9, 2026, 8:47 a.m.
Created at: March 4, 2026, 7:44 p.m.