Triple

T1960093
Position Surface form Disambiguated ID Type / Status
Subject Filipa Moniz Perestrelo E42364 entity
Predicate givenName P17 FINISHED
Object Filipa E42364 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: Filipa | Statement: [Filipa Moniz Perestrelo, givenName, Filipa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Filipa
Context triple: [Filipa Moniz Perestrelo, givenName, Filipa]
  • A. Filipa Moniz Perestrelo chosen
    Filipa Moniz Perestrelo was a Portuguese noblewoman from a prominent maritime family who became the wife of explorer Christopher Columbus.
  • B. Madalena
    Madalena is a neighborhood in the Brazilian city of Recife, known for its urban character and local commerce.
  • C. Lucia Moniz
    Lucia Moniz is a Portuguese actress and singer best known internationally for her role in the film "Love Actually."
  • D. 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.
  • E. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • 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_69a8870eea088190a38781990812a9bc completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb37f737881908130bb828affcaa2 completed March 7, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae031ef4e48190af93dfd6f33184d3 completed March 8, 2026, 11:15 p.m.
Created at: March 4, 2026, 7:36 p.m.