Triple

T21758718
Position Surface form Disambiguated ID Type / Status
Subject Sir William Gage, 2nd Baronet E537105 entity
Predicate landholdingsIn P113753 FINISHED
Object Sussex 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: Sussex | Statement: [Sir William Gage, 2nd Baronet, landholdingsIn, Sussex]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sussex
Context triple: [Sir William Gage, 2nd Baronet, landholdingsIn, Sussex]
  • A. Sussex
    Sussex is a traditional British dual-purpose chicken breed valued for both its meat and egg production.
  • B. Sussex chosen
    Sussex is a historic county in South East England, known for its coastal resorts, rolling South Downs, and rich medieval and maritime heritage.
  • C. East Sussex
    East Sussex is a county in South East England known for its English Channel coastline, the South Downs, and historic towns such as Hastings and Lewes.
  • D. West Sussex
    West Sussex is a county in South East England known for its mix of coastal towns, rural countryside, and historic market settlements.
  • E. Essex
    Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
  • 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_69e0c46eab808190b848242d63a17c47 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f01d902c9881908051904e44a136af completed April 28, 2026, 2:38 a.m.
Created at: April 16, 2026, 6:50 p.m.