Triple

T15115747
Position Surface form Disambiguated ID Type / Status
Subject Ariane Wilhelmina Máxima Inés E361034 entity
Predicate givenName P17 FINISHED
Object Inés E398718 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: Inés | Statement: [Ariane Wilhelmina Máxima Inés, givenName, Inés]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inés
Context triple: [Ariane Wilhelmina Máxima Inés, givenName, Inés]
  • A. Inés chosen
    Inés is a feminine given name, especially common in Spanish-speaking countries, derived from the name Agnes.
  • B. Pilar
    Pilar is a Spanish royal, known formally as Infanta Pilar, Duchess of Badajoz, and a member of the House of Bourbon.
  • C. Pilar
    Pilar is the introspective female protagonist of Paulo Coelho’s novel "By the River Piedra I Sat Down and Wept," whose spiritual and emotional journey drives the story.
  • D. Pilar
    Pilar is a coastal town on Siargao Island in the Philippines, known for its fishing communities and access to popular surfing and eco-tourism spots.
  • E. Pilar
    Pilar is a Spanish feminine given name, often associated with religious devotion to Our Lady of the Pillar and traditionally used in Spain and Spanish-speaking countries.
  • 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_69d85a0491ec8190830960be8fafb994 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0058f4fb88190a3d446a466aebcf1 completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69febfe3fe0081909d9d3a293373254b completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 3:05 a.m.