Triple

T3417161
Position Surface form Disambiguated ID Type / Status
Subject Eurowings E72036 entity
Predicate callsign P1565 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: [Eurowings, callsign, EUROWINGS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EUROWINGS
Context triple: [Eurowings, callsign, 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. Interflug
    Interflug was the state-owned national airline of East Germany, operating international and domestic flights primarily within the Eastern Bloc during the Cold War.
  • C. Air Europa
    Air Europa is a Spanish airline that operates domestic and international flights, serving as one of Spain’s major carriers and a member of the SkyTeam alliance.
  • D. 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.
  • E. Lufthansa
    Lufthansa is Germany’s largest airline and a major global carrier known for its extensive international network and role in shaping modern airline alliances.
  • 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_69ad85ad38e48190b7660c5118a35289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb92c20fc81909b5debced20ec083 completed March 8, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360c285688190a264fcb4ab271b82 completed March 13, 2026, 12:56 a.m.
Created at: March 8, 2026, 3:15 p.m.