Triple

T7572851
Position Surface form Disambiguated ID Type / Status
Subject Freiburg im Breisgau E179286 entity
Predicate hasLandmark P105 FINISHED
Object Schwabentor
Schwabentor is a historic medieval city gate in Freiburg im Breisgau, Germany, known as one of the city’s iconic architectural landmarks.
E673785 NE FINISHED

How this triple was built (4 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: Schwabentor | Statement: [Freiburg im Breisgau, hasLandmark, Schwabentor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwabentor
Context triple: [Freiburg im Breisgau, hasLandmark, Schwabentor]
  • A. Schottentor
    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. Spittlertor
    Spittlertor is a historic city gate in Nuremberg, Germany, known as part of the medieval fortifications that once protected the old town.
  • C. Burgtor
    Burgtor is a historic city gate in Lübeck, Germany, notable as part of the city’s medieval fortifications and Hanseatic architectural heritage.
  • D. Frauentor
    Frauentor is a historic city gate in Nuremberg, Germany, notable as one of the main entrances through the medieval fortifications into the old town.
  • E. Hallesches Tor
    Hallesches Tor is a major Berlin U-Bahn interchange station in the Kreuzberg district, serving as a key hub for multiple subway lines.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Schwabentor
Triple: [Freiburg im Breisgau, hasLandmark, Schwabentor]
Generated description
Schwabentor is a historic medieval city gate in Freiburg im Breisgau, Germany, known as one of the city’s iconic architectural landmarks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Schwabentor
Target entity description: Schwabentor is a historic medieval city gate in Freiburg im Breisgau, Germany, known as one of the city’s iconic architectural landmarks.
  • A. Schottentor
    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. Spittlertor
    Spittlertor is a historic city gate in Nuremberg, Germany, known as part of the medieval fortifications that once protected the old town.
  • C. Burgtor
    Burgtor is a historic city gate in Lübeck, Germany, notable as part of the city’s medieval fortifications and Hanseatic architectural heritage.
  • D. Frauentor
    Frauentor is a historic city gate in Nuremberg, Germany, notable as one of the main entrances through the medieval fortifications into the old town.
  • E. Hallesches Tor
    Hallesches Tor is a major Berlin U-Bahn interchange station in the Kreuzberg district, serving as a key hub for multiple subway lines.
  • F. None of above. chosen

Provenance (5 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_69c69f316e50819081a271c85c06f918 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f94710a0819094508356b8d610ab completed March 27, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856ea9a2c8190a81762ac509c4c97 completed March 28, 2026, 10:32 p.m.
NEDg Description generation batch_69c8587b461c819081b63e71b533547a completed March 28, 2026, 10:38 p.m.
NED2 Entity disambiguation (via description) batch_69c858fd9d4081909bb2072fcc3e3836 completed March 28, 2026, 10:41 p.m.
Created at: March 27, 2026, 3:51 p.m.