Triple

T8031547
Position Surface form Disambiguated ID Type / Status
Subject Falkeplatz E186993 entity
Predicate hasNearbyStreet P8235 FINISHED
Object Brückenstraße E52499 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: Brückenstraße | Statement: [Falkeplatz, hasNearbyStreet, Brückenstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brückenstraße
Context triple: [Falkeplatz, hasNearbyStreet, Brückenstraße]
  • A. Brückenstraße chosen
    Brückenstraße is a street in Chemnitz, Germany, known for being the prominent urban backdrop in front of the iconic Karl Marx Monument.
  • B. Breite Straße
    Breite Straße is a historic main street in the medieval town of Goslar, Germany, known for its traditional half-timbered houses and central role in the old town.
  • C. Breite Straße
    Breite Straße is a historic main street in the former city of Cölln, now part of central Berlin, known for its role in the early urban development of the area.
  • D. Rosenbergstraße
    Rosenbergstraße is a street that lends its name to and hosts the Rosenbergstraße campus.
  • E. Berger Straße
    Berger Straße is a prominent and lively shopping and dining street in Frankfurt am Main, known for its mix of boutiques, cafés, bars, and traditional Hessian pubs.
  • 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_69ca82ae2d1081909dbfee42b41db419 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3eef921081908d0ea21f142c175a completed March 31, 2026, 3:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccecc7c7f08190981e00342325a6da completed April 1, 2026, 10 a.m.
Created at: March 30, 2026, 5:22 p.m.