Triple

T9508936
Position Surface form Disambiguated ID Type / Status
Subject The Mall at Millenia E229340 entity
Predicate owner P347 FINISHED
Object The Forbes Company E804229 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: The Forbes Company | Statement: [The Mall at Millenia, owner, The Forbes Company]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Forbes Company
Context triple: [The Mall at Millenia, owner, The Forbes Company]
  • A. The Forbes Company chosen
    The Forbes Company is a U.S.-based real estate development firm known for creating and operating upscale, luxury shopping malls.
  • B. MacAndrews & Forbes
    MacAndrews & Forbes is a private holding company controlled by Ronald Perelman, known for its diversified investments across industries such as consumer products, entertainment, and defense.
  • C. Fox Company
    Fox Company is a rifle company within the U.S. Marine Corps’ 2nd Battalion, 4th Marines, known for its role in infantry combat operations.
  • D. Fox Company
    Fox Company is a rifle company within the 2nd Battalion, 1st Marines, a storied infantry battalion of the United States Marine Corps.
  • E. Burroughs Corporation
    Burroughs Corporation was a major American business equipment and computer company, best known as one of the early mainframe manufacturers and a predecessor of Unisys.
  • 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_69ca847611c48190a28c028644198c75 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9855c5e48190a7d8d39b6d601679 completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c1092bc8190917d71e2b6f62c25 completed April 4, 2026, 5:36 p.m.
Created at: March 30, 2026, 7:58 p.m.