Triple

T3690592
Position Surface form Disambiguated ID Type / Status
Subject Heiligensee E78332 entity
Predicate traversedBy P225 FINISHED
Object Bundesstraße 96 E318592 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: Bundesstraße 96 | Statement: [Heiligensee, traversedBy, Bundesstraße 96]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bundesstraße 96
Context triple: [Heiligensee, traversedBy, Bundesstraße 96]
  • A. Bundesstraße 96 chosen
    Bundesstraße 96 is a major German federal highway running in a north–south direction, notably connecting Berlin with the Baltic Sea island of Rügen.
  • B. Bundesstraße 7
    Bundesstraße 7 is a major German federal highway running east–west across several states and connecting numerous cities and regions.
  • C. Bundesstraße 10
    Bundesstraße 10 is a major federal highway in southern Germany that runs east–west and connects several important cities in the states of Baden-Württemberg and Rhineland-Palatinate.
  • D. Bundesstraße 3
    Bundesstraße 3 is a major German federal highway running north–south through several states and connecting numerous cities and towns.
  • E. Bundesstraße
    A Bundesstraße is a major federal highway in Germany that connects cities and regions and is ranked below the Autobahn in the national road network.
  • 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_69ad85e285a081908f8cbfa9e2ed9b75 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4e6147c8190ae358e8cc94f479c completed March 8, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3c9e9c08190bd97642ccf39b172 completed March 14, 2026, 2:11 a.m.
Created at: March 8, 2026, 3:26 p.m.