Triple

T17322949
Position Surface form Disambiguated ID Type / Status
Subject Conte E420605 entity
Predicate femaleEquivalentTitle P1613 FINISHED
Object Contessa E703000 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: Contessa | Statement: [Conte, femaleEquivalentTitle, Contessa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Contessa
Context triple: [Conte, femaleEquivalentTitle, Contessa]
  • A. Contessa Francesca
    Contessa Francesca is a central fictional noblewoman featured as the protagonist in the swashbuckling pirate novel "The Spanish Main."
  • B. Contessina
    Contessina is a feminine Italian given name historically associated with the influential Medici family of Renaissance Florence.
  • C. Countess chosen
    A countess is a noblewoman, typically ranking below a marchioness and above a viscountess, often holding the female equivalent of an earl or count’s title in European aristocracy.
  • D. Rosabella
    Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
  • E. Contessa Estelle Marie Carandini di Sarzano
    Contessa Estelle Marie Carandini di Sarzano was an Italian-born noblewoman and socialite best known as the aristocratic mother of actor Sir Christopher Lee.
  • 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_69d889d22b848190a4663d0b8f8f76e7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e439d0cf2481908a018593ef39fd18 completed April 19, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a018c4a6630819082998cf754e8361f completed May 11, 2026, 7:59 a.m.
Created at: April 10, 2026, 5:43 a.m.