Triple

T15048776
Position Surface form Disambiguated ID Type / Status
Subject Mall of Georgia E379298 entity
Predicate hasAnchorTenant P11754 FINISHED
Object Von Maur E90349 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: Von Maur | Statement: [Mall of Georgia, hasAnchorTenant, Von Maur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Von Maur
Context triple: [Mall of Georgia, hasAnchorTenant, Von Maur]
  • A. Von Maur chosen
    Von Maur is an American upscale department store chain known for its high-end fashion, customer service, and presence in major shopping malls across the Midwest and South.
  • B. Burdine
    Burdine is the respondent in the U.S. Supreme Court employment discrimination case Texas Department of Community Affairs v. Burdine, which clarified the burden of proof framework in Title VII disparate treatment claims.
  • C. Hecht's
    Hecht's was a regional department store chain in the Mid-Atlantic United States, later absorbed into Macy's.
  • D. Dunnigan
    Dunnigan is a small unincorporated community in Yolo County, California, known primarily as a rural agricultural area along Interstate 5.
  • E. Fischer’s
    Fischer’s is a renowned London restaurant known for its classic Viennese café style, serving Central European dishes in an elegant, old-world setting.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69deda8f71988190b4fe7f7de4ccb798 completed April 15, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9de83b648190ba437c0fac164ec6 completed May 9, 2026, 2:37 a.m.
Created at: April 10, 2026, 3 a.m.