Triple

T5348458
Position Surface form Disambiguated ID Type / Status
Subject Bundesstraße 3 E124112 entity
Predicate connectsWith P37 FINISHED
Object Northeim E408729 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: Northeim | Statement: [Bundesstraße 3, connectsWith, Northeim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Northeim
Context triple: [Bundesstraße 3, connectsWith, Northeim]
  • A. Northeim chosen
    Northeim is a town in Lower Saxony, Germany, known for its medieval old town and location in the Leine River valley.
  • B. Lüneburg
    Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
  • C. Delmenhorst
    Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
  • D. Nordhausen
    Nordhausen is a historic town in central Germany known for its medieval architecture, former role as a key trading center, and association with the nearby Mittelbau-Dora concentration camp site.
  • E. Braunschweig
    Braunschweig is a historic city in northern Germany known for its medieval architecture, cultural institutions, and role as an important economic and scientific center.
  • 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_69bd464be27081908807b40b75c1bbae completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85ef75148190815461c2a49302e9 completed March 20, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04c916df08190a95e3320ab364b52 completed March 22, 2026, 8:09 p.m.
Created at: March 20, 2026, 2:01 p.m.