Triple

T16913806
Position Surface form Disambiguated ID Type / Status
Subject PRG E410269 entity
Predicate servesAsHubFor P423 FINISHED
Object Czech Airlines E33033 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: Czech Airlines | Statement: [PRG, servesAsHubFor, Czech Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Czech Airlines
Context triple: [PRG, servesAsHubFor, Czech Airlines]
  • A. Czech Airlines chosen
    Czech Airlines is the national flag carrier of the Czech Republic, operating scheduled passenger flights across Europe and to select long-haul destinations.
  • 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. MÁV
    MÁV is the Hungarian State Railways company, responsible for operating most of Hungary’s national rail network and related infrastructure.
  • D. Croatia Airlines
    Croatia Airlines is the national flag carrier of Croatia, operating domestic and international passenger flights across Europe.
  • E. JAT Yugoslav Airlines
    JAT Yugoslav Airlines was the former national flag carrier of Yugoslavia, operating extensive domestic and international routes across Europe and beyond during much of the 20th century.
  • 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3ca3f1a2c8190a512ccc09a080eb4 completed April 18, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7be679c8190b9d0b0b9cfe185d3 completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:30 a.m.