Triple

T16246527
Position Surface form Disambiguated ID Type / Status
Subject Bahnhofsviertel E394383 entity
Predicate hasLandmark P105 FINISHED
Object Weserstraße NE NERFINISHED

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: Weserstraße | Statement: [Bahnhofsviertel, hasLandmark, Weserstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weserstraße
Context triple: [Bahnhofsviertel, hasLandmark, Weserstraße]
  • A. Langenstraße
    Langenstraße is a district or neighborhood within the town of Rüthen in North Rhine-Westphalia, Germany.
  • B. Voßstraße
    Voßstraße is a street in central Berlin, Germany, historically notable for hosting key government buildings of the German Empire and Nazi era near Potsdamer Platz and the government quarter.
  • C. Malchower Chaussee
    Malchower Chaussee is a main road in Berlin that serves as a key access route to the Malchow locality.
  • D. Hedderichstraße chosen
    Hedderichstraße is a street in Frankfurt am Main, Germany, located in the Sachsenhausen district and connected to the city’s public transport network.
  • E. Lange Straße
    Lange Straße is a central street in Oldenburg, Germany, known as a main shopping thoroughfare and for landmarks such as the historic Lappan tower.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e245931074819096f38003da70f271 completed April 17, 2026, 2:37 p.m.
Created at: April 10, 2026, 5:04 a.m.