Triple

T354727
Position Surface form Disambiguated ID Type / Status
Subject Svetlana Alliluyeva E7517 entity
Predicate residence P75 FINISHED
Object Cambridge, England E492 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: Cambridge, England | Statement: [Svetlana Alliluyeva, residence, Cambridge, England]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cambridge, England
Context triple: [Svetlana Alliluyeva, residence, Cambridge, England]
  • A. Cambridge, England chosen
    Cambridge, England is a historic university city on the River Cam renowned for the University of Cambridge and its longstanding contributions to education, science, and culture.
  • B. Cambridge city center
    Cambridge city center is the main commercial and cultural hub of Cambridge, Massachusetts, encompassing historic districts, universities, shops, and restaurants.
  • C. Middlesex, England
    Middlesex, England is a historic county in southeast England that once encompassed much of what is now Greater London.
  • D. Oxford
    Oxford is a historic English city renowned for its prestigious university, distinctive architecture, and long-standing academic and cultural influence.
  • E. Cambridgeshire, England
    Cambridgeshire, England is a historic county in eastern England known for its rural landscapes and as the home of the prestigious University of Cambridge.
  • 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_69a2e7e696948190bebc966535995e45 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2eb8312f4819084dc222e665fded3 completed Feb. 28, 2026, 1:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69a44cb342c08190bcdcdbecf6ba4244 completed March 1, 2026, 2:26 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.