Triple

T10671043
Position Surface form Disambiguated ID Type / Status
Subject Frankfurt public transport network E251484 entity
Predicate hasHub P2413 FINISHED
Object Hauptwache E393821 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: Hauptwache | Statement: [Frankfurt public transport network, hasHub, Hauptwache]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hauptwache
Context triple: [Frankfurt public transport network, hasHub, Hauptwache]
  • A. Hauptwache chosen
    Hauptwache is a central square and major transportation hub in Frankfurt am Main, known for its historic guardhouse building and busy commercial surroundings.
  • B. Der Turm
    Der Turm is a late Expressionist drama by Austrian writer Hugo von Hofmannsthal that reimagines Shakespeare’s "The Tempest" in a dark, politically charged setting.
  • C. Das Schloss
    Das Schloss is a prominent shopping mall in Berlin known for its distinctive architecture and wide range of retail and dining options.
  • D. Hausmannsturm
    Hausmannsturm is a historic tower in Dresden that serves as a prominent landmark and viewing point associated with the city’s royal residence complex.
  • E. Schlossturm
    Schlossturm is a historic castle tower and prominent architectural landmark located on the Rhine riverfront in Düsseldorf’s Old Town.
  • 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_69d6aa5b0d2881909584b20efc5877f0 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6f8648a248190a3bd284c569152e4 completed April 9, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9886e3f108190bb6f17d4e2f394ef completed April 10, 2026, 11:31 p.m.
Created at: April 8, 2026, 9:09 p.m.