Triple

T15904639
Position Surface form Disambiguated ID Type / Status
Subject Ricky Butler E385677 entity
Predicate neighborOf P350 FINISHED
Object Ray Peterson E390785 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: Ray Peterson | Statement: [Ricky Butler, neighborOf, Ray Peterson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ray Peterson
Context triple: [Ricky Butler, neighborOf, Ray Peterson]
  • A. Ray Peterson chosen
    Ray Peterson is the paranoid yet well-meaning suburban homeowner played by Tom Hanks in the dark comedy film "The 'Burbs."
  • B. Dwight Hauser
    Dwight Hauser was an American screenwriter and film producer known for his work on mid-20th-century family and adventure films, including several Disney nature and animal features.
  • C. Phil Morrison
    Phil Morrison is an American film and television director best known for his work on indie films like "Junebug" and various acclaimed music videos and commercials.
  • D. Glen Bateman
    Glen Bateman is a retired sociology professor and key survivor character in Stephen King's post-apocalyptic novel "The Stand," known for his analytical perspective on the collapse and rebuilding of society.
  • E. Jeff Morrow
    Jeff Morrow was an American actor best known for his roles in mid-20th-century films and television, particularly in biblical epics and science fiction movies.
  • 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_69d86da686e4819097cbf3b1fc2d881d completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1563f74d88190a3d92ca0ad46e867 completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3bb7d608190babbea74a9ca9f4c completed May 9, 2026, 11:31 p.m.
Created at: April 10, 2026, 4:52 a.m.