Triple

T16329383
Position Surface form Disambiguated ID Type / Status
Subject Ines E396507 entity
Predicate hasSpellingVariant P457 FINISHED
Object Inés (with acute accent) 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 (with acute accent) | Statement: [Ines, hasSpellingVariant, Inés (with acute accent)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inés (with acute accent)
Context triple: [Ines, hasSpellingVariant, Inés (with acute accent)]
  • A. Inés chosen
    Inés is a feminine given name, especially common in Spanish-speaking countries, derived from the name Agnes.
  • B. Ines
    Ines is a feminine given name, commonly used in various European and Latin American countries, that is a variant of the name Agnes.
  • C. Inés García
    Inés García was the wife of Mexican general and politician Antonio López de Santa Anna, associated with his personal and political life during 19th-century Mexico.
  • D. María del Carmen
    María del Carmen is a Spanish-language feminine given name commonly used in Hispanic cultures, often in honor of Our Lady of Mount Carmel.
  • E. Inés de Suárez
    Inés de Suárez is a station on Line 6 of the Santiago Metro in Santiago, Chile.
  • 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_69d87f255b788190a400eba031dd85d8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2c4ddc5608190b24fe2e871691470 completed April 17, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a002da915ac8190820acbe0db72c8a1 completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:07 a.m.