Triple

T14375381
Position Surface form Disambiguated ID Type / Status
Subject AutoScout24 GmbH E356460 entity
Predicate name P16 FINISHED
Object AutoScout24 GmbH E356460 NE 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: AutoScout24 GmbH | Statement: [AutoScout24 GmbH, name, AutoScout24 GmbH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AutoScout24 GmbH
Context triple: [AutoScout24 GmbH, name, AutoScout24 GmbH]
  • A. AutoScout24 GmbH chosen
    AutoScout24 GmbH is a major European online marketplace specializing in the listing and trading of new and used vehicles.
  • B. AutoScout24
    AutoScout24 is a major European online marketplace specializing in buying and selling new and used cars.
  • C. Immobilien Scout GmbH
    Immobilien Scout GmbH is a leading German online real estate marketplace platform, best known for its property listings and related services for buyers, renters, and sellers.
  • D. Renk AG
    Renk AG is a German engineering company specializing in high-performance transmissions, gear units, and drive technology for military and industrial applications.
  • E. Ola Auto
    Ola Auto is a ride-hailing service segment of Ola Cabs that connects passengers with auto-rickshaw drivers via the Ola mobile app.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de900949fc81909be0da1734c46645 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c5514688190be90776c8764d4f3 completed May 8, 2026, 2:37 a.m.
Created at: April 10, 2026, 1:16 a.m.