Triple

T23070391
Position Surface form Disambiguated ID Type / Status
Subject Mariona Caldentey E575177 entity
Predicate givenName P17 FINISHED
Object Mariona 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: Mariona | Statement: [Mariona Caldentey, givenName, Mariona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mariona
Context triple: [Mariona Caldentey, givenName, Mariona]
  • A. Mariona Caldentey chosen
    Mariona Caldentey is a Spanish professional footballer, primarily an attacking midfielder or forward, known for her creativity and technical skill for both FC Barcelona and the Spain women's national team.
  • B. Alfonsa
    Alfonsa is a feminine given name, primarily used in Romance-language cultures, derived from the masculine name Alfonso.
  • C. Sanchia
    Sanchia was a 13th-century noblewoman from the House of Provence who became Queen of the Romans through her marriage to Richard of Cornwall.
  • D. Piera
    Piera is a municipality in the comarca of Anoia in Catalonia, Spain, known for its historic town center and surrounding agricultural landscape.
  • E. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • 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_69e245bd6e4c8190bb8942245b68cad5 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18c5f17348190ab92cfdae9bcaeba completed April 29, 2026, 4:43 a.m.
Created at: April 17, 2026, 3:56 p.m.