Triple

T9903336
Position Surface form Disambiguated ID Type / Status
Subject Bamburgh E182340 entity
Predicate hasHistoricalName P2834 FINISHED
Object Bebbanburg E182340 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: Bebbanburg | Statement: [Bamburgh, hasHistoricalName, Bebbanburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bebbanburg
Context triple: [Bamburgh, hasHistoricalName, Bebbanburg]
  • A. Kingswear
    Kingswear is a village and civil parish on the south bank of the River Dart in Devon, England, known for its picturesque harbor and ferry link to Dartmouth.
  • B. Senlac Hill
    Senlac Hill is the site near Hastings in East Sussex, England, where the decisive Battle of Hastings was fought in 1066, leading to the Norman Conquest.
  • C. Bamburgh chosen
    Bamburgh is a historic coastal village in Northumberland, England, best known for its imposing medieval castle overlooking the North Sea.
  • D. Bettany
    Bettany is an English surname most notably associated with actor Paul Bettany.
  • E. Tilbury Fort
    Tilbury Fort is a historic artillery fort on the north bank of the River Thames in Essex, England, best known for defending London from seaborne attack from the 16th century onwards.
  • 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_69ca82876f8081909cf75df0f99bb13f completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cdb4e4f92c81908e38509416f19c78 completed April 2, 2026, 12:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1eb2778bc81909d7e09da718d9afa completed April 5, 2026, 4:55 a.m.
Created at: March 30, 2026, 8:40 p.m.