Triple

T5510524
Position Surface form Disambiguated ID Type / Status
Subject Martin Chemnitz E144550 entity
Predicate burialPlace P196 FINISHED
Object Braunschweig E72622 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: Braunschweig | Statement: [Martin Chemnitz, burialPlace, Braunschweig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Braunschweig
Context triple: [Martin Chemnitz, burialPlace, Braunschweig]
  • A. Braunschweig chosen
    Braunschweig is a historic city in northern Germany known for its medieval architecture, cultural institutions, and role as an important economic and scientific center.
  • B. Hildesheim
    Hildesheim is a historic city in northern Germany renowned for its medieval architecture and UNESCO-listed Romanesque churches.
  • C. Bremen
    Bremen is a city-state in northwestern Germany comprising the cities of Bremen and Bremerhaven, known for its historic Hanseatic heritage and major port on the Weser River.
  • D. Bielefeld
    Bielefeld is a major city in northwestern Germany known for its industrial heritage, university, and the tongue-in-cheek “Bielefeld conspiracy” meme claiming it does not exist.
  • E. Lüneburg
    Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
  • 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_69c008f6b5048190a09064116062cf69 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f4cbc2c819091fcbff5f39ceeb4 completed March 22, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a1308a548190b49a8212c3f3f7f0 completed March 23, 2026, 2:10 a.m.
Created at: March 22, 2026, 3:33 p.m.