Triple

T20996035
Position Surface form Disambiguated ID Type / Status
Subject Dorey Walker E517151 entity
Predicate employer P7 FINISHED
Object Macy's NE NERFINISHED

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: Macy's | Statement: [Dorey Walker, employer, Macy's]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Macy's
Context triple: [Dorey Walker, employer, Macy's]
  • A. Macy's chosen
    Macy's is a major American department store chain known for its wide range of apparel, home goods, and its flagship store in New York City.
  • B. Marshalls
    Marshalls is a major American off-price department store chain known for selling brand-name clothing, home goods, and accessories at discounted prices.
  • C. Nordstrom
    Nordstrom is a leading American luxury department store chain known for its high-end fashion, quality customer service, and nationwide retail presence.
  • D. Lord & Taylor
    Lord & Taylor is a historic American department store chain known for its upscale fashion offerings and flagship presence on New York City's Fifth Avenue.
  • E. J. C. Penney
    J. C. Penney was an American businessman and entrepreneur best known as the founder of the JCPenney department store chain.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b5006e2881909fc2383f841740cc completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc1fd5d48190a56981cee95ebd69 completed April 21, 2026, 4:25 a.m.
Created at: April 16, 2026, 1:50 p.m.