Triple

T568720
Position Surface form Disambiguated ID Type / Status
Subject TXL E13614 entity
Predicate servedAsFocusCityFor P1655 FINISHED
Object Lufthansa E48740 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: Lufthansa | Statement: [TXL, servedAsFocusCityFor, Lufthansa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lufthansa
Context triple: [TXL, servedAsFocusCityFor, Lufthansa]
  • A. Lufthansa chosen
    Lufthansa is Germany’s largest airline and a major global carrier known for its extensive international network and role in shaping modern airline alliances.
  • B. 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.
  • 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. Eurowings
    Eurowings is a German low-cost airline and Lufthansa subsidiary that operates short- and long-haul flights across Europe and selected international destinations.
  • E. Air Berlin
    Air Berlin was a now-defunct major German airline that operated extensive domestic and international routes, once serving as Germany’s second-largest carrier.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d28af148190acad3cfb809ff2f2 completed March 1, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a510380e048190b2f8f08abf07a594 completed March 2, 2026, 4:21 a.m.
Created at: March 1, 2026, 7:33 p.m.