Triple

T8741846
Position Surface form Disambiguated ID Type / Status
Subject S7 Group E207520 entity
Predicate ownsMaintenanceBusiness P13496 FINISHED
Object S7 Technics E754446 NE FINISHED

How this triple was built (3 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: S7 Technics | Statement: [S7 Group, ownsMaintenanceBusiness, S7 Technics]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S7 Technics
Context triple: [S7 Group, ownsMaintenanceBusiness, S7 Technics]
  • A. S7 Technics chosen
    S7 Technics is a Russian aircraft maintenance, repair, and overhaul (MRO) company that services both S7 Airlines and other carriers.
  • B. S7
    S7 is the IATA airline designator for S7 Airlines, a major Russian carrier based in Novosibirsk.
  • C. S7
    S7 is a Berlin S-Bahn rapid transit line that runs across the city, connecting key districts between Potsdam and Ahrensfelde.
  • D. Siemens S70
    The Siemens S70 is a modern low-floor light rail vehicle widely used in North American urban transit systems.
  • E. Siemens SD100
    The Siemens SD100 is a light rail vehicle model built by Siemens for use on urban trolley and light rail systems such as the San Diego Trolley.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: ownsMaintenanceBusiness
Context triple: [S7 Group, ownsMaintenanceBusiness, S7 Technics]
  • A. ownsService
    Indicates that one entity has ownership or control over a particular service.
  • B. hasMaintenanceService
    Indicates that an entity receives or is covered by a maintenance service provided by another entity.
  • C. hasMaintenance
    Indicates that an entity is subject to, associated with, or requires a particular maintenance activity or maintenance record.
  • D. ownsOrManages chosen
    Indicates that one entity has ownership of, or managerial control over, another entity.
  • E. maintenanceAuthority
    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 (4 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d6fd5dc8190906b7147f27c5d46 completed March 31, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf518750948190a42ad8fc352ac851 completed April 3, 2026, 5:35 a.m.
PD Predicate disambiguation batch_69cc457322b481908712a9630a17b954 completed March 31, 2026, 10:06 p.m.
Created at: March 30, 2026, 6:38 p.m.