Triple

T17777503
Position Surface form Disambiguated ID Type / Status
Subject Maintenance Directorate of Mexico City Metro E443809 entity
Predicate typeOfMaintenance P118531 FINISHED
Object preventive maintenance 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: preventive maintenance | Statement: [Maintenance Directorate of Mexico City Metro, typeOfMaintenance, preventive maintenance]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typeOfMaintenance
Context triple: [Maintenance Directorate of Mexico City Metro, typeOfMaintenance, preventive maintenance]
  • A. maintenanceType chosen
    Indicates the specific category or kind of maintenance activity associated with an entity or relationship.
  • B. hasMaintenanceType
    Indicates the specific category or kind of maintenance associated with an asset, component, or maintenance event.
  • C. hasMaintenance
    Indicates that an entity is subject to, associated with, or requires a particular maintenance activity or maintenance record.
  • D. hasMaintenanceService
    Indicates that an entity receives or is covered by a maintenance service provided by another entity.
  • E. maintenancePractice
    Indicates the specific actions or methods used to preserve, repair, or optimize the condition or performance of something over time.
  • 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_69d8b9ef17708190bdf7e2adbf14ddc2 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4871e06a481909cf6d59e49dc21c5 completed April 19, 2026, 7:41 a.m.
PD Predicate disambiguation batch_69e3d8d8e538819084f1584426b41d5e completed April 18, 2026, 7:17 p.m.
Created at: April 10, 2026, 10:12 a.m.