Triple

T15726404
Position Surface form Disambiguated ID Type / Status
Subject Werderscher Markt E381228 entity
Predicate near P350 FINISHED
Object Gendarmenmarkt E151220 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: Gendarmenmarkt | Statement: [Werderscher Markt, near, Gendarmenmarkt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gendarmenmarkt
Context triple: [Werderscher Markt, near, Gendarmenmarkt]
  • A. Gendarmenmarkt chosen
    Gendarmenmarkt is a historic and architecturally renowned square in central Berlin, famous for its ensemble of the German and French Cathedrals and the Konzerthaus.
  • B. Breitscheidplatz
    Breitscheidplatz is a major public square and transport hub in central Berlin, known for the Kaiser Wilhelm Memorial Church and its surrounding shopping and entertainment district.
  • C. Holstentorplatz
    Holstentorplatz is a public square in Lübeck, Germany, situated prominently in front of the historic Holstentor city gate and serving as a central traffic and visitor hub.
  • D. Marienplatz
    Marienplatz is the central square in Munich, Germany, renowned as the city's historic heart and a major hub for cultural events, tourism, and public life.
  • E. Charlottenplatz
    Charlottenplatz is a major public square and traffic junction in central Stuttgart, 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_69d86d9cdb648190bf3171be0bd7d872 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fb357a88190a92641c8a8c20573 completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82f8b88081909855d3da0346fa25 completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:46 a.m.