Triple

T13812342
Position Surface form Disambiguated ID Type / Status
Subject Charonne workshop E331923 entity
Predicate maintenanceFor P26299 FINISHED
Object trains operating on Paris Métro Line 2 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: trains operating on Paris Métro Line 2 | Statement: [Charonne workshop, maintenanceFor, trains operating on Paris Métro Line 2]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: maintenanceFor
Context triple: [Charonne workshop, maintenanceFor, trains operating on Paris Métro Line 2]
  • A. maintenance
    Indicates that an entity performs, requires, or is involved in upkeep, repair, or preservation activities for another entity or system.
  • B. maintenancePractice
    Indicates the specific actions or methods used to preserve, repair, or optimize the condition or performance of something over time.
  • C. hasMaintenance
    Indicates that an entity is subject to, associated with, or requires a particular maintenance activity or maintenance record.
  • D. maintenanceFeature
    Indicates that one entity serves as a maintenance-related feature, capability, or component associated with another entity.
  • E. maintenanceAuthority chosen
    Indicates that one entity has the responsibility or official power to maintain, service, or keep another entity in proper working condition.
  • 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_69de027198f8819095da3e714ac241f5 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.