Triple

T1426745
Position Surface form Disambiguated ID Type / Status
Subject Frederick Weyerhaeuser E30349 entity
Predicate familyName P18 FINISHED
Object Weyerhaeuser E1563 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: Weyerhaeuser | Statement: [Frederick Weyerhaeuser, familyName, Weyerhaeuser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weyerhaeuser
Context triple: [Frederick Weyerhaeuser, familyName, Weyerhaeuser]
  • A. Weyerhaeuser Company chosen
    Weyerhaeuser Company is a major American timberland and forest products company, historically one of the world’s largest private owners of softwood timber.
  • B. Georgia-Pacific
    Georgia-Pacific is a major American pulp and paper company known for producing tissue, packaging, building products, and related chemicals.
  • C. Darby Lumber Company
    Darby Lumber Company was a Georgia lumber manufacturer that served as the private business defendant in the landmark U.S. Supreme Court case United States v. Darby, which expanded federal power under the Commerce Clause.
  • D. International Paper
    International Paper is a leading global producer of renewable fiber-based packaging, pulp, and paper products.
  • E. UPM
    UPM is the Polytechnic University of Madrid, a leading Spanish public university specializing in engineering, architecture, and technology.
  • 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_69a498fb823c8190a67ce4c4837e641a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c4be7d208190bcfb46239bd72e56 completed March 1, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad016708bc8190af01b10a0f0d6942 completed March 8, 2026, 4:56 a.m.
Created at: March 1, 2026, 8 p.m.