Triple

T14755225
Position Surface form Disambiguated ID Type / Status
Subject Margareten E346712 entity
Predicate borderedBy P224 FINISHED
Object Landstraße E346710 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: Landstraße | Statement: [Margareten, borderedBy, Landstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Landstraße
Context triple: [Margareten, borderedBy, Landstraße]
  • A. Landstraße chosen
    Landstraße is Vienna’s 3rd municipal district, a central urban area known for its mix of historic architecture, embassies, and major transport hubs.
  • B. Torstraße
    Torstraße is a major street in central Berlin, Germany, known for its mix of historic architecture, shops, restaurants, and nightlife.
  • C. Salzstraße
    Salzstraße is a historic street in Münster, Germany, known as one of the city’s traditional merchant and baroque thoroughfares.
  • D. Brüderstraße
    Brüderstraße is a historic street in the old town of Görlitz, Germany, known for its well-preserved architecture and connection to the central Obermarkt square.
  • E. Via Krupp
    Via Krupp is a famous historic footpath on the Italian island of Capri, known for its dramatic series of hairpin bends carved into the cliffside overlooking the sea.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7d59df08190a86da5048358bd6e completed April 14, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb9e1b8481909abea3daabe91302 completed May 8, 2026, 3:05 p.m.
Created at: April 10, 2026, 1:30 a.m.