Triple

T13817494
Position Surface form Disambiguated ID Type / Status
Subject Cortes Superiores de Justicia E332054 entity
Predicate tieneSalasEspecializadas P466 FINISHED
Object salas civiles 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: salas civiles | Statement: [Cortes Superiores de Justicia, tieneSalasEspecializadas, salas civiles]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: tieneSalasEspecializadas
Context triple: [Cortes Superiores de Justicia, tieneSalasEspecializadas, salas civiles]
  • A. hasSpecialty chosen
    Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
  • B. hasSpecialist
    Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
  • C. hasSpecialCollections
    Indicates that an entity possesses or maintains distinct, curated collections that are set apart from its general holdings.
  • D. hasOperatingTheatres
    Indicates that an entity possesses or includes one or more operating theatres as part of its facilities or infrastructure.
  • E. institutionSpecialization
    Indicates that an institution focuses on, is dedicated to, or has expertise in a particular field, domain, or area of activity.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0281bb988190803ee195f430b9c8 completed April 14, 2026, 9:01 a.m.
PD Predicate disambiguation batch_69dbc862e9608190bd8a3d883959b7e4 completed April 12, 2026, 4:29 p.m.
Created at: April 9, 2026, 10:12 p.m.