Triple

T14479179
Position Surface form Disambiguated ID Type / Status
Subject Police Academy 2: Their First Assignment E359055 entity
Predicate writer P1360 FINISHED
Object David Sheffield E335262 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: David Sheffield | Statement: [Police Academy 2: Their First Assignment, writer, David Sheffield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Sheffield
Context triple: [Police Academy 2: Their First Assignment, writer, David Sheffield]
  • A. David Sheffield chosen
    David Sheffield is an American comedy writer best known for co-writing several Eddie Murphy films and contributing to classic Saturday Night Live sketches.
  • B. Alan Ricks
    Alan Ricks is an American architect and co-founder of MASS Design Group, known for his work on socially driven, community-focused design projects around the world.
  • C. Michael Wood
    Michael Wood is a British historian and broadcaster known for his popular television documentaries and books on English history.
  • D. Alan Fairford
    Alan Fairford is a conscientious young Scottish lawyer who serves as one of the central protagonists in Sir Walter Scott’s novel "Redgauntlet."
  • E. Graham Carr
    Graham Carr is a Canadian academic and administrator who serves as the president of Concordia University in Montreal.
  • 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_69d827966698819082e140837737501d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de924a576c819098351efabdb779b1 completed April 14, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd64a257488190818c65c1cc84c4b5 completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:20 a.m.