Triple

T14736907
Position Surface form Disambiguated ID Type / Status
Subject Maria José de Lancastre E346234 entity
Predicate placeOfResidence P75 FINISHED
Object Pisa E32982 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: Pisa | Statement: [Maria José de Lancastre, placeOfResidence, Pisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pisa
Context triple: [Maria José de Lancastre, placeOfResidence, Pisa]
  • A. Pisa chosen
    Pisa is a historic Italian city in Tuscany best known for its iconic Leaning Tower and as a significant center of medieval trade, learning, and architecture.
  • B. Pisa
    Pisa is an ancient city in the Peloponnese region of Greece, historically significant as a center near Olympia and associated with early Greek myth and athletics.
  • C. Florence
    Florence is the birth name of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics brand.
  • D. Florence
    Florence is a historic Italian city renowned as the cradle of the Renaissance, celebrated for its art, architecture, and cultural influence.
  • E. Florence
    Florence is an unincorporated community within Florence Township in New Jersey, known primarily as a residential area along the Delaware River.
  • 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_69d822e6f1c88190bc494d491a907114 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec73114cc819088e1101b689fc70b completed April 14, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24ae3d6c819080c015ebc6bc9af0 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:29 a.m.