Triple

T1594365
Position Surface form Disambiguated ID Type / Status
Subject Berlin Brandenburg Airport E34245 entity
Predicate hasHubAirline P423 FINISHED
Object Eurowings E72036 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: Eurowings | Statement: [Berlin Brandenburg Airport, hasHubAirline, Eurowings]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eurowings
Context triple: [Berlin Brandenburg Airport, hasHubAirline, Eurowings]
  • A. Eurowings chosen
    Eurowings is a German low-cost airline and Lufthansa subsidiary that operates short- and long-haul flights across Europe and selected international destinations.
  • B. Lufthansa CityLine
    Lufthansa CityLine is a German regional airline and Lufthansa subsidiary that operates short- and medium-haul routes across Europe, primarily feeding traffic into Lufthansa’s main hubs.
  • C. S7 Airlines
    S7 Airlines is a major Russian airline based in Novosibirsk that operates extensive domestic and international routes, particularly across Russia, Europe, and Asia.
  • D. Wizz Air
    Wizz Air is a Hungarian ultra-low-cost airline known for operating an extensive network of budget flights across Europe and surrounding regions.
  • E. Transavia
    Transavia is a Dutch low-cost airline operating scheduled and charter flights across Europe and North Africa.
  • 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_69a885fdcb9c819081ce6f0b8cd477dd completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9092aed308190a0198a0fb977a9e5 completed March 5, 2026, 4:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8ab5e8b88190b95af87391e5bb16 completed March 8, 2026, 2:41 p.m.
Created at: March 4, 2026, 7:27 p.m.