Triple

T19661664
Position Surface form Disambiguated ID Type / Status
Subject Votivkirche E472095 entity
Predicate locatedIn P40 FINISHED
Object Alsergrund 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: Alsergrund | Statement: [Votivkirche, locatedIn, Alsergrund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alsergrund
Context triple: [Votivkirche, locatedIn, Alsergrund]
  • A. Alsergrund chosen
    Alsergrund is the 9th district of Vienna, Austria, known for its historic architecture, cultural institutions, and proximity to the city center.
  • B. Adlersruhe
    Adlersruhe is a high-altitude spot on Austria’s Grossglockner often used as a staging point for climbers ascending the mountain.
  • C. Brigittenau
    Brigittenau is the 20th district of Vienna, Austria, known for its dense urban character and location between the Danube Canal and the Danube River.
  • D. Bergmannkiez
    Bergmannkiez is a popular, lively neighborhood in Berlin known for its historic architecture, café-lined streets, and vibrant cultural scene.
  • E. Ochsengarten
    Ochsengarten is a small alpine village in the Tyrolean Ötztal region of Austria, known for its mountain scenery and access to hiking and skiing.
  • 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_69d8e51395348190ac1416d46dfc6db0 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6414a667c81909aad04a737773c7e completed April 20, 2026, 3:07 p.m.
Created at: April 10, 2026, 1:45 p.m.