Triple

T6578041
Position Surface form Disambiguated ID Type / Status
Subject Inés Mendoza E157218 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: [Inés Mendoza, givenName, Inés]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inés
Context triple: [Inés Mendoza, 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 strong-willed, perceptive Spanish guerrilla fighter who plays a central role in Ernest Hemingway’s novel "For Whom the Bell Tolls."
  • 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_69c6882b3a108190b3a9eb343ae4162c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae74fd90819091d67eec6381d5e0 completed March 27, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cba5cc708190a8748160a7878b8f completed March 27, 2026, 6:25 p.m.
Created at: March 27, 2026, 1:54 p.m.