Triple

T19854024
Position Surface form Disambiguated ID Type / Status
Subject Elisenda de Montcada E477083 entity
Predicate givenName P17 FINISHED
Object Elisenda 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: Elisenda | Statement: [Elisenda de Montcada, givenName, Elisenda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elisenda
Context triple: [Elisenda de Montcada, givenName, Elisenda]
  • A. Elisenda de Montcada chosen
    Elisenda de Montcada was a 14th-century Catalan noblewoman who became Queen consort of Aragon through her marriage to King James II.
  • B. María de Montserrat
    María de Montserrat is the given name of Montserrat Caballé, the renowned Spanish operatic soprano celebrated for her bel canto technique and powerful, expressive voice.
  • C. Alfonsa
    Alfonsa is a feminine given name, primarily used in Romance-language cultures, derived from the masculine name Alfonso.
  • D. Leocadia
    Leocadia is a painting by Francisco Goya depicting a somberly dressed woman believed to be his companion, Leocadia Weiss, mourning beside a tomb.
  • E. Ignasi
    Ignasi is a masculine given name of Catalan origin, commonly used in Spanish-speaking regions.
  • 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_69d8e51d39d081909bcfafeaaf3d2fcc completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6586aa1dc8190b6cfe051a57e338b completed April 20, 2026, 4:46 p.m.
Created at: April 10, 2026, 1:51 p.m.