Triple

T11752944
Position Surface form Disambiguated ID Type / Status
Subject Theater an der Wien E279452 entity
Predicate locatedIn P40 FINISHED
Object Naschmarkt area E571418 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: Naschmarkt area | Statement: [Theater an der Wien, locatedIn, Naschmarkt area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naschmarkt area
Context triple: [Theater an der Wien, locatedIn, Naschmarkt area]
  • A. Neumarkt area
    The Neumarkt area is a central historic square and commercial district in Dresden, Germany, known for its reconstructed Baroque architecture and proximity to major landmarks like the Frauenkirche.
  • B. Karmeliterplatz area chosen
    The Karmeliterplatz area is a central square and surrounding neighborhood in Vienna’s Leopoldstadt district, known for its market, local shops, and community life.
  • C. Untermarkt
    Untermarkt is the historic lower market square in Görlitz, Germany, known for its well-preserved medieval and Renaissance architecture.
  • D. Untermarkt
    Untermarkt is a historic central market square in the Saxon mining town of Freiberg, Germany, known for its medieval architecture and role as a focal point of urban life.
  • E. Grüner Markt
    Grüner Markt is a central marketplace and public square in the Bavarian city of Fürth, known for its local vendors and historic urban setting.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a509c2448190b0deb7ed29c3a73f completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f01a21559c819097d0287dd8e2f411 completed April 28, 2026, 2:23 a.m.
Created at: April 8, 2026, 9:41 p.m.