Triple

T29408180
Position Surface form Disambiguated ID Type / Status
Subject Ley General de Educación de Uruguay E745825 entity
Predicate regulaRelaciónCon P84787 FINISHED
Object Administración Nacional de Educación Pública NE NERFINISHED

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: Administración Nacional de Educación Pública | Statement: [Ley General de Educación de Uruguay, regulaRelaciónCon, Administración Nacional de Educación Pública]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: regulaRelaciónCon
Context triple: [Ley General de Educación de Uruguay, regulaRelaciónCon, Administración Nacional de Educación Pública]
  • A. allyRelation
    Indicates a cooperative, supportive relationship in which the entities act as allies toward shared or aligned goals.
  • B. subjectRelation chosen
    Indicates that one entity stands in a specified relational role or connection to another entity.
  • C. conditionRelatesTo
    Indicates that one condition is relevant, connected, or applicable to another condition or contextual factor.
  • D. relatedRule
    Indicates that one rule is connected or associated with another rule, typically through some logical, structural, or referential relationship.
  • E. laterRelationWith
    Indicates that one entity stands in a temporal relationship to another such that it occurs or exists at a later time than the other.
  • 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_69f0a79eb7d081908c67197a5f347e68 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f9fd6834cc8190aa27153d6a99f3bb completed May 5, 2026, 2:23 p.m.
PD Predicate disambiguation batch_69f7cf769338819092a5f42653dcc956 completed May 3, 2026, 10:43 p.m.
Created at: April 28, 2026, 2:55 p.m.