Triple

T14381039
Position Surface form Disambiguated ID Type / Status
Subject Siemens EuroSprinter E356600 entity
Predicate operator P179 FINISHED
Object MÁV 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 | Statement: [Siemens EuroSprinter, operator, MÁV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MÁV
Context triple: [Siemens EuroSprinter, operator, MÁV]
  • A. MÁV chosen
    MÁV is the Hungarian State Railways company, responsible for operating most of Hungary’s national rail network and related infrastructure.
  • B. 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.
  • 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. 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.
  • E. Czech Airlines
    Czech Airlines is the national flag carrier of the Czech Republic, operating scheduled passenger flights across Europe and to select long-haul destinations.
  • 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_69de900bbfb08190a1e56f281a2374c0 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c590660819090652e75418f2747 completed May 8, 2026, 2:37 a.m.
Created at: April 10, 2026, 1:16 a.m.