Triple

T3802803
Position Surface form Disambiguated ID Type / Status
Subject Graz E91728 entity
Predicate hasAirport P105 FINISHED
Object Graz Airport E281525 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: Graz Airport | Statement: [Graz, hasAirport, Graz Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Graz Airport
Context triple: [Graz, hasAirport, Graz Airport]
  • A. Graz Airport chosen
    Graz Airport is an international airport in southeastern Austria serving the city of Graz and the surrounding Styria region.
  • B. Linz Airport
    Linz Airport is the main international airport serving the city of Linz and the surrounding Upper Austria region.
  • C. Salzburg Airport
    Salzburg Airport is an international airport in western Austria serving the city of Salzburg and the surrounding region, including nearby towns such as Anif.
  • D. Innsbruck Airport
    Innsbruck Airport is a regional international airport in western Austria serving the city of Innsbruck and the surrounding Tyrolean Alps, known for its challenging approach amid mountainous terrain and seasonal tourism traffic.
  • E. Vienna International Airport
    Vienna International Airport is Austria’s largest and busiest airport, serving as the primary international gateway to Vienna and a major hub for Central and Eastern Europe.
  • 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_69aed96354f48190a768966d6bd19b04 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee7bacf2881908198a77063d15d16 completed March 9, 2026, 3:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f06889c88190ab4d8da7f0dfeadd completed March 14, 2026, 5:21 a.m.
Created at: March 9, 2026, 3:15 p.m.