Triple

T13536654
Position Surface form Disambiguated ID Type / Status
Subject Eiserner Steg E323278 entity
Predicate hasViewOf P854 FINISHED
Object Museumsufer E59735 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: Museumsufer | Statement: [Eiserner Steg, hasViewOf, Museumsufer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Museumsufer
Context triple: [Eiserner Steg, hasViewOf, Museumsufer]
  • A. Museumsufer chosen
    Museumsufer is Frankfurt am Main’s renowned museum district along the River Main, known for its dense concentration of major art, cultural, and historical museums.
  • B. Museum by the Stream
    Museum by the Stream is the English name for Museum aan de Stroom, a major contemporary museum and architectural landmark in Antwerp, Belgium.
  • C. Muzeum
    Muzeum is a major interchange station in the Prague Metro system, located beneath Wenceslas Square and serving as a key hub for lines A and C.
  • D. The Museum
    The Museum is an art exhibition space within Tokyo’s Bunkamura cultural complex, known for hosting a wide range of domestic and international art shows.
  • E. Museumeiland
    Museumeiland is an artificial island in Groningen, Netherlands, primarily known as the striking, water-surrounded site of the Groninger Museum complex.
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafbe39948190808062d4eff91841 completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d9a448c81908fa57a909a9097f7 completed May 3, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:45 p.m.