Triple

T11711052
Position Surface form Disambiguated ID Type / Status
Subject Cécilia Ciganer-Albéniz E278373 entity
Predicate givenName P17 FINISHED
Object Cécilia E135814 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: Cécilia | Statement: [Cécilia Ciganer-Albéniz, givenName, Cécilia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cécilia
Context triple: [Cécilia Ciganer-Albéniz, givenName, Cécilia]
  • A. Cecilia chosen
    Cecilia is a feminine given name of Latin origin, traditionally associated with Saint Cecilia, the patron saint of music.
  • B. Cécile
    Cécile is the sensitive and central protagonist of the French film "Cible émouvante," around whom the story’s emotional and narrative developments revolve.
  • C. Oriana
    Oriana is a feminine given name of Latin origin, often associated with meanings like "golden" or "dawn."
  • D. Arabella
    Arabella is a feminine given name of Latin origin, often associated with elegance and used in various English-speaking cultures.
  • E. 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.
  • 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_69d6aaff2ce88190b4a1e4b341ad5377 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a49f072c81909c6a964a92e5bc0c completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69f0196916e081908671e79765d03778 completed April 28, 2026, 2:20 a.m.
Created at: April 8, 2026, 9:40 p.m.