Triple

T16687710
Position Surface form Disambiguated ID Type / Status
Subject Lorna Crozier E405507 entity
Predicate spouse P13 FINISHED
Object Patrick Lane E70516 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: Patrick Lane | Statement: [Lorna Crozier, spouse, Patrick Lane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patrick Lane
Context triple: [Lorna Crozier, spouse, Patrick Lane]
  • A. Patrick Lane chosen
    Patrick Lane was a Canadian poet and novelist renowned for his powerful, often dark explorations of nature, memory, and personal struggle.
  • B. Scott Lane
    Scott Lane is a participant featured in the documentary series "Shots in the Dark," which follows photographers working on the overnight crime beat.
  • C. Martin Lane
    Martin Lane is a central father figure and newspaper editor on the 1960s American sitcom "The Patty Duke Show."
  • D. Patrick Leyland
    Patrick Leyland is the son of longtime Major League Baseball manager Jim Leyland and has been involved in professional baseball himself as a player and coach.
  • E. Mike Lane
    Mike Lane is the charismatic male stripper and aspiring entrepreneur portrayed by Channing Tatum in the Magic Mike film series.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ea75df481909a7ebb9b2a9d0afd completed April 18, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a45af7c8190bfe09dd0e0573573 completed May 10, 2026, 1:38 p.m.
Created at: April 10, 2026, 5:19 a.m.