Triple

T15261143
Position Surface form Disambiguated ID Type / Status
Subject Sire de Grugy E364776 entity
Predicate basedAt P40 FINISHED
Object Sussex, England E361007 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: Sussex, England | Statement: [Sire de Grugy, basedAt, Sussex, England]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sussex, England
Context triple: [Sire de Grugy, basedAt, Sussex, England]
  • A. Suffolk, England
    Suffolk, England is a historic rural county in East Anglia known for its medieval towns, coastal landscapes, and agricultural heritage.
  • B. Berkshire, England
    Berkshire, England is a historic county in South East England known for its royal connections, including Windsor Castle, and its picturesque Thames-side towns.
  • C. 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.
  • D. Sussex
    Sussex is a traditional British dual-purpose chicken breed valued for both its meat and egg production.
  • E. Surrey, England
    Surrey, England is a county in South East England known for its affluent towns, leafy suburbs, and proximity to London.
  • 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_69d85a0f08408190b3c3259ae35d79d2 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0084e85a08190b8e63598b9f6a535 completed April 15, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fee5fb8b30819096d31ba5884715c9 completed May 9, 2026, 7:44 a.m.
Created at: April 10, 2026, 3:14 a.m.