Triple

T22029069
Position Surface form Disambiguated ID Type / Status
Subject The Statute Law Database E544038 entity
Predicate dataSource P409 FINISHED
Object Stationery Office 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: Stationery Office | Statement: [The Statute Law Database, dataSource, Stationery Office]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stationery Office
Context triple: [The Statute Law Database, dataSource, Stationery Office]
  • A. His Majesty's Stationery Office chosen
    His Majesty's Stationery Office is a former UK government department and official publisher responsible for producing and distributing state documents, legislation, and official publications.
  • B. Staples
    Staples is a small city in Guadalupe County, Texas, known for its rural character and location along the San Marcos River.
  • C. Staples
    Staples is a small central Minnesota city that serves as a regional hub for transportation, education, and local commerce.
  • D. Staples
    Staples is a surname most prominently associated with American singer and civil rights activist Mavis Staples.
  • E. OfficeMax
    OfficeMax is a major American office supplies retail chain offering products such as stationery, furniture, and technology for businesses and consumers.
  • 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_69e11e2f98c8819083e11eab90942a78 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127ebf6d48190b84e7a45bbf9049c completed April 28, 2026, 9:34 p.m.
Created at: April 16, 2026, 8:24 p.m.