Triple

T3875177
Position Surface form Disambiguated ID Type / Status
Subject Fürther Innenstadt E92483 entity
Predicate hasLandmark P105 FINISHED
Object Grüner Markt E14685 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: Grüner Markt | Statement: [Fürther Innenstadt, hasLandmark, Grüner Markt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grüner Markt
Context triple: [Fürther Innenstadt, hasLandmark, Grüner Markt]
  • A. Grüner Markt chosen
    Grüner Markt is a central marketplace and public square in the Bavarian city of Fürth, known for its local vendors and historic urban setting.
  • B. Viktualienmarkt
    Viktualienmarkt is a famous open-air food and produce market in the historic center of Munich, known for its diverse stalls, beer garden, and traditional Bavarian atmosphere.
  • C. Kohlmarkt
    Kohlmarkt is a historic and upscale shopping street in Vienna’s city center, known for its luxury boutiques and elegant architecture.
  • D. Untermarkt
    Untermarkt is the historic lower market square in Görlitz, Germany, known for its well-preserved medieval and Renaissance architecture.
  • E. Hauptmarkt
    Hauptmarkt is the historic main market square in Nuremberg, Germany, known for its daily market, Christmas fair, and prominent landmarks such as the Schöner Brunnen.
  • 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_69aed967448c819086c4b358d37b25aa completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec706434819095e0d2b376adb548 completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5124f095881909143b624128ff569 completed March 14, 2026, 7:46 a.m.
Created at: March 9, 2026, 3:20 p.m.