Triple

T8638531
Position Surface form Disambiguated ID Type / Status
Subject Hero of the Republic of Cuba E204583 entity
Predicate genderedForms P17779 FINISHED
Object Héroe de la República de Cuba LITERAL 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: Héroe de la República de Cuba | Statement: [Hero of the Republic of Cuba, genderedForms, Héroe de la República de Cuba]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: genderedForms
Context triple: [Hero of the Republic of Cuba, genderedForms, Héroe de la República de Cuba]
  • A. genderedFormOf chosen
    Indicates that one term is a gender-specific variant or inflected form corresponding to another, more neutral or differently gendered term.
  • B. genderNeutralForm
    Indicates that one entity is a gender-neutral linguistic form or expression corresponding to another, more gendered form.
  • C. hasFemaleFormOf
    Indicates that one entity is the specifically female version or form of another, more general or differently gendered entity.
  • D. hasGrammaticalGender
    Indicates that one entity assigns or possesses a specific grammatical gender in relation to another entity (such as a word, phrase, or linguistic unit).
  • E. hasMasculineForm
    Indicates that an entity has a corresponding masculine grammatical or lexical form.
  • F. None of above.

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_69ca834ca1c88190a11ffb0200342fac completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc47944d1c819081f448f14d04bf9d completed March 31, 2026, 10:15 p.m.
PD Predicate disambiguation batch_69cc455d6d448190a2da2a319ac78c37 completed March 31, 2026, 10:06 p.m.
Created at: March 30, 2026, 6:28 p.m.