Triple

T10351663
Position Surface form Disambiguated ID Type / Status
Subject MÁV E243894 entity
Predicate hasSubsidiary P254 FINISHED
Object MÁV-START E857878 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: MÁV-START | Statement: [MÁV, hasSubsidiary, MÁV-START]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MÁV-START
Context triple: [MÁV, hasSubsidiary, MÁV-START]
  • A. MÁV chosen
    MÁV is the Hungarian State Railways company, responsible for operating most of Hungary’s national rail network and related infrastructure.
  • B. Vienna AirportLines
    Vienna AirportLines is a dedicated airport bus service that provides direct connections between Vienna International Airport and various key locations in and around Vienna.
  • C. Flughafen Wien AG
    Flughafen Wien AG is an Austrian publicly listed company that operates and manages Vienna International Airport and related airport services.
  • D. Austrian Airlines
    Austrian Airlines is the flag carrier airline of Austria, operating an extensive network of European and long-haul flights from its main hub in Vienna.
  • E. Malev Hungarian Airlines
    Malev Hungarian Airlines was the former national flag carrier of Hungary, operating scheduled passenger flights across Europe and beyond until its closure in 2012.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9489f9481908fc1c818e81c1cc2 completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d8dc10284c8190bcce0f058b88ef0e completed April 10, 2026, 11:16 a.m.
Created at: April 6, 2026, 11:57 a.m.