Triple

T18542807
Position Surface form Disambiguated ID Type / Status
Subject Love-Letters Between a Nobleman and His Sister E453141 entity
Predicate protagonist P268 FINISHED
Object Silvia NE NERFINISHED

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: Silvia | Statement: [Love-Letters Between a Nobleman and His Sister, protagonist, Silvia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Silvia
Context triple: [Love-Letters Between a Nobleman and His Sister, protagonist, Silvia]
  • A. Silvia chosen
    Silvia is a feminine given name used in various languages, often associated with the Latin word for "forest" or "woods."
  • B. Leonora
    Leonora is a remote mining town in Western Australia’s Goldfields-Esperance region, historically significant for its goldfields and outback heritage.
  • C. Leonora
    Leonora is a feminine given name used in various cultures, often considered a variant of Eleanor or Leonore.
  • 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. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d388b0c881908e610a1c45b52640 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e534b80fc081908488417787d1b166 completed April 19, 2026, 8:02 p.m.
Created at: April 10, 2026, 11:38 a.m.