Triple

T17320292
Position Surface form Disambiguated ID Type / Status
Subject Hershey Bears E420540 entity
Predicate city P40 FINISHED
Object Hershey NE ONNED1

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: Hershey | Statement: [Hershey Bears, city, Hershey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hershey
Context triple: [Hershey Bears, city, Hershey]
  • A. The Hershey Company
    The Hershey Company is a major American chocolate and confectionery manufacturer best known for products like Hershey’s chocolate bars, Reese’s, and Kit Kat in the U.S.
  • B. Mars, Incorporated
    Mars, Incorporated is a major American multinational manufacturer of confectionery, pet food, and other food products, known for brands such as M&M’s, Snickers, and Pedigree.
  • C. Hershey Entertainment and Resorts Company chosen
    Hershey Entertainment and Resorts Company is a privately held hospitality and entertainment company that operates theme parks, resorts, and related attractions associated with the Hershey chocolate brand.
  • D. Nabisco
    Nabisco is a major American snack food company best known for iconic brands like Oreo cookies and Ritz crackers.
  • E. Hersey
    Hersey is a surname most notably associated with John Hersey, the American writer and journalist renowned for his work "Hiroshima."
  • 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_69d889d22b848190a4663d0b8f8f76e7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e439a066b481908e8aee1885809eba completed April 19, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01954cfd048190b201c5e457c2a4a2 in_progress May 11, 2026, 8:37 a.m.
Created at: April 10, 2026, 5:43 a.m.