Triple

T64729
Position Surface form Disambiguated ID Type / Status
Subject Old Irish E1286 entity
Predicate hasGenderCategory P2577 FINISHED
Object masculine 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: masculine | Statement: [Old Irish, hasGenderCategory, masculine]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasGenderCategory
Context triple: [Old Irish, hasGenderCategory, masculine]
  • A. genderCategories chosen
    Indicates the classification of an entity into one or more gender-related categories or identities.
  • B. hasNumberOfGenders
    Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
  • C. hasGenderFocus
    Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
  • D. sexOrGender
    Indicates that one entity has a specified biological sex or socially constructed gender identity.
  • E. hasGenderPolicy
    Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
  • 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_69a24ba4f760819081f6638a3c70538a completed Feb. 28, 2026, 1:57 a.m.
NER Named-entity recognition batch_69a2516eda54819090f5c14384d4eab1 completed Feb. 28, 2026, 2:22 a.m.
PD Predicate disambiguation batch_69a24ea5c140819080409a968c8d2ce8 completed Feb. 28, 2026, 2:10 a.m.
Created at: Feb. 28, 2026, 2:02 a.m.