Triple

T4669253
Position Surface form Disambiguated ID Type / Status
Subject Lady Diana Cooper E102921 entity
Predicate birthPlace P1 FINISHED
Object London, England E1817 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: London, England | Statement: [Lady Diana Cooper, birthPlace, London, England]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: London, England
Context triple: [Lady Diana Cooper, birthPlace, London, England]
  • A. London, England chosen
    London, England is the capital and largest city of the United Kingdom, renowned as a global center for finance, culture, and politics.
  • B. London
    London is a major Ethereum network upgrade that introduced significant changes to the protocol’s fee market and transaction pricing mechanisms.
  • C. York, England
    York, England is a historic walled city in northern England renowned for its medieval architecture, including York Minster, and its rich Roman and Viking heritage.
  • D. Allondon
    Allondon is a small river in western Switzerland and neighboring France, known for flowing through the Geneva region and its natural, relatively unspoiled surroundings.
  • E. London Victoria
    London Victoria is a major central London railway terminus and Underground station, serving as a key hub for commuter, regional, and Gatwick Airport services.
  • 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_69bd43d9cba4819086c1ab1c2d9d2133 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6340ce548190bd436c59f28227d7 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69be104a596c8190903c208c892da186 completed March 21, 2026, 3:28 a.m.
Created at: March 20, 2026, 1:15 p.m.