Triple

T14761749
Position Surface form Disambiguated ID Type / Status
Subject Dornier Do J Wal E346878 entity
Predicate usedBy P260 FINISHED
Object Swissair E205529 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: Swissair | Statement: [Dornier Do J Wal, usedBy, Swissair]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swissair
Context triple: [Dornier Do J Wal, usedBy, Swissair]
  • A. Swissair chosen
    Swissair was the former national airline of Switzerland, renowned for its high service standards and extensive international route network until its collapse in 2001.
  • B. Swiss International Air Lines
    Swiss International Air Lines is the flag carrier airline of Switzerland, operating a global network of flights primarily from its hub in Zurich.
  • C. 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.
  • D. 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.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7f207dc819088a53f717736a121 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24b1ff0c81908d5dffbaf86c3ca3 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:30 a.m.