Triple

T19394932
Position Surface form Disambiguated ID Type / Status
Subject Wien Hauptbahnhof E485162 entity
Predicate locatedIn P40 FINISHED
Object Favoriten NE NERFINISHED

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: Favoriten | Statement: [Wien Hauptbahnhof, locatedIn, Favoriten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Favoriten
Context triple: [Wien Hauptbahnhof, locatedIn, Favoriten]
  • A. Favoriten chosen
    Favoriten is the 10th district of Vienna, Austria, known as a large, densely populated residential area with a diverse population and a mix of historic and modern urban development.
  • B. Fave
    Fave is a Nigerian singer and songwriter known for her emotive vocals and Afropop-influenced sound.
  • C. La favorita
    La favorita is a grand opera in four acts by Gaetano Donizetti, renowned for its dramatic bel canto style and emotionally powerful vocal writing.
  • D. Graveyard of Favorites
    Graveyard of Favorites is the famous nickname for Saratoga Race Course, reflecting its long history of upsets in which heavily favored horses are unexpectedly defeated.
  • E. Faydi
    Faydi is a village located within the Shekhan District in the Kurdistan Region of northern Iraq.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e61b47630881909ba390888b8779f6 completed April 20, 2026, 12:25 p.m.
Created at: April 10, 2026, 1:36 p.m.