Triple

T21310586
Position Surface form Disambiguated ID Type / Status
Subject Autostrada A4 E525321 entity
Predicate managedInSectionsBy P29724 FINISHED
Object various concessionary companies 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: various concessionary companies | Statement: [Autostrada A4, managedInSectionsBy, various concessionary companies]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: managedInSectionsBy
Context triple: [Autostrada A4, managedInSectionsBy, various concessionary companies]
  • A. managedIn chosen
    Indicates that one entity is administered, operated, or overseen within the scope, control, or jurisdiction of another entity.
  • B. associatedWithSection
    Indicates that one entity is linked or connected to a particular section within a larger structure or context.
  • C. roleInSection106
    Indicates that an entity has a specific role or involvement within the context of Section 106 (typically of a legal or regulatory framework).
  • D. manageThrough
    Indicates that one entity exercises control, direction, or administration over another entity or process by means of an intermediary entity, channel, or mechanism.
  • E. associatedWorkSection
    Indicates that one work or resource is related to a specific section or part of another work.
  • 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_69e0b518b8948190ad69cf9a8784d397 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e75aab14f08190949e1407eb2b3e67 completed April 21, 2026, 11:08 a.m.
PD Predicate disambiguation batch_69e61612ab748190a72b8703b938abcb completed April 20, 2026, 12:03 p.m.
Created at: April 16, 2026, 4:09 p.m.