Triple

T3757556
Position Surface form Disambiguated ID Type / Status
Subject The 'Burbs E82083 entity
Predicate character P662 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: [The 'Burbs, character, Ray Peterson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ray Peterson
Context triple: [The 'Burbs, character, 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. William A. Petersen
    William A. Petersen was a 19th-century Washington, D.C. tailor and boardinghouse owner whose home became historically significant as the place where President Abraham Lincoln died.
  • C. John Gibbon
    John Gibbon was a 19th-century United States Army officer and Civil War general who later played a key role in the Indian Wars, including campaigns against the Nez Perce.
  • D. Ronald N. Perlman
    Ronald N. Perlman is an American actor best known for his distinctive deep voice and leading roles in works such as the "Hellboy" films and the television series "Beauty and the Beast."
  • E. Peter D. Graves
    Peter D. Graves is a film producer best known for his work on major Hollywood action and science fiction movies, including Terminator Salvation.
  • 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_69ad8b1db40081908b61ffa6b78afd4d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcbc04d348190b0e4a90d18bdd160 completed March 8, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503e6c48881909ac813e603175eb0 completed March 14, 2026, 6:44 a.m.
Created at: March 8, 2026, 3:35 p.m.