Triple

T13536956
Position Surface form Disambiguated ID Type / Status
Subject Römer city hall E323284 entity
Predicate nearby P350 FINISHED
Object Alte Nikolaikirche E297605 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: Alte Nikolaikirche | Statement: [Römer city hall, nearby, Alte Nikolaikirche]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alte Nikolaikirche
Context triple: [Römer city hall, nearby, Alte Nikolaikirche]
  • A. Alte Nikolaikirche chosen
    Alte Nikolaikirche is a historic Lutheran church in Frankfurt’s old town, notable for its medieval architecture and prominent location on the Römerberg square.
  • B. Nikolaikirche
    Nikolaikirche is Berlin’s oldest church, a historic Gothic landmark located in the Nikolaiviertel district.
  • C. Nikolaikirche
    Nikolaikirche is a historic church in the German town of Eschwege, notable for its traditional architecture and role as a central Protestant parish church.
  • D. Nikolaikirche
    Nikolaikirche is a historic church in the German town of Korbach, notable for its medieval architecture and role as a prominent local landmark.
  • E. Nikolaikirche
    Nikolaikirche is a historic Protestant church in the German city of Siegen, notable for its distinctive hilltop location and characteristic architecture.
  • 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.