Triple

T5049696
Position Surface form Disambiguated ID Type / Status
Subject Arabella Kennedy E113753 entity
Predicate givenName P17 FINISHED
Object Arabella E368923 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: Arabella | Statement: [Arabella Kennedy, givenName, Arabella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arabella
Context triple: [Arabella Kennedy, givenName, Arabella]
  • A. Arabella chosen
    Arabella is a feminine given name of Latin origin, often associated with elegance and used in various English-speaking cultures.
  • B. Arabella
    Arabella is a romantic opera in three acts by Richard Strauss, first performed in 1933, known for its lush orchestration and exploration of love and social expectations in 19th-century Vienna.
  • C. Rosabella
    Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
  • D. Cecilia
    Cecilia is a feminine given name of Latin origin, traditionally associated with Saint Cecilia, the patron saint of music.
  • E. Ricarda
    Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
  • 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_69bd44391fc48190a311ce9c826c209b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd74249a8c8190952680aee06a9286 completed March 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea480fee88190a4302301259f29ba completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:37 p.m.