Triple

T1211334
Position Surface form Disambiguated ID Type / Status
Subject Flivver E26005 entity
Predicate relatedTerm P37 FINISHED
Object Tin Lizzie E25545 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: Tin Lizzie | Statement: [Flivver, relatedTerm, Tin Lizzie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tin Lizzie
Context triple: [Flivver, relatedTerm, Tin Lizzie]
  • A. Tin Lizzie chosen
    Tin Lizzie is the popular nickname for the Ford Model T, the early 20th-century automobile that revolutionized mass car production and personal transportation.
  • B. Ozzie
    Ozzie is the nickname of Ozzie Nelson, the American bandleader, actor, and television producer best known for creating and starring in the classic sitcom "The Adventures of Ozzie and Harriet."
  • C. Willie
    Willie is the first name of Willie Nelson, the iconic American country music singer-songwriter and cultural figure.
  • D. Lilly Belle
    Lilly Belle is a steam locomotive that operates on the Walt Disney World Railroad at the Magic Kingdom theme park in Florida.
  • E. Dwighty
    Dwighty is a fan nickname for Dwight Fairfield, a nervous but resourceful survivor character from the horror game Dead by Daylight.
  • 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_69a4948331fc8190b531ac9bec71c491 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bde581308190bbe30683bf6c48c3 completed March 1, 2026, 10:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f43a12c8190a1ba90eefafd6bbc completed March 7, 2026, 7:40 p.m.
Created at: March 1, 2026, 7:46 p.m.