Triple

T19661591
Position Surface form Disambiguated ID Type / Status
Subject Schottenring E472093 entity
Predicate near P350 FINISHED
Object Schottentor 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: Schottentor | Statement: [Schottenring, near, Schottentor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schottentor
Context triple: [Schottenring, near, Schottentor]
  • A. Schottentor chosen
    Schottentor is a historic former city gate area in Vienna that now serves as a major public transport hub and landmark at the edge of the Innere Stadt.
  • B. Schwabentor
    Schwabentor is a historic medieval city gate in Freiburg im Breisgau, Germany, known as one of the city’s iconic architectural landmarks.
  • C. Stadttor
    Stadttor is a prominent modern office and government building in Düsseldorf, Germany, known for its distinctive glass architecture and role as a landmark of the MedienHafen area.
  • D. Rieder Tor
    Rieder Tor is a historic city gate in Donauwörth, Germany, and one of the town’s best-known architectural landmarks.
  • E. Spittlertor
    Spittlertor is a historic city gate in Nuremberg, Germany, known as part of the medieval fortifications that once protected the old town.
  • 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_69d8e51395348190ac1416d46dfc6db0 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6414a667c81909aad04a737773c7e completed April 20, 2026, 3:07 p.m.
Created at: April 10, 2026, 1:45 p.m.