Triple

T12012906
Position Surface form Disambiguated ID Type / Status
Subject Naturhistorisches Museum Wien E285948 entity
Predicate locatedIn P40 FINISHED
Object Innere Stadt E69717 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: Innere Stadt | Statement: [Naturhistorisches Museum Wien, locatedIn, Innere Stadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Innere Stadt
Context triple: [Naturhistorisches Museum Wien, locatedIn, Innere Stadt]
  • A. Innere Stadt chosen
    Innere Stadt is the historic first district and city center of Vienna, Austria, known for its medieval street layout, grand boulevards, and concentration of major cultural and political landmarks.
  • B. Innenstadt
    Innenstadt is the central urban district of Frankfurt am Main, known as the city’s historic core and primary commercial area.
  • C. Innere Neustadt
    Innere Neustadt is a historic central district of Dresden, Germany, known for its Baroque architecture, cultural venues, and vibrant urban life along the Elbe River.
  • D. Stadtmitte
    Stadtmitte is the central urban district of the town of Bad Honnef in North Rhine-Westphalia, Germany.
  • E. Stadtmitte
    Stadtmitte is the central urban district and main downtown area of the town of Eberswalde in Germany.
  • 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_69d6ab45a368819084fce08bf0dc3705 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903d884488190b4450a98088208ef completed April 10, 2026, 2:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69f48b363c6481908c8414c1eecc14f5 completed May 1, 2026, 11:15 a.m.
Created at: April 8, 2026, 9:46 p.m.