Triple

T10305409
Position Surface form Disambiguated ID Type / Status
Subject Ravensburg E241739 entity
Predicate hasLandmark P105 FINISHED
Object Blaserturm
Blaserturm is a historic medieval watch and bell tower that serves as one of the most recognizable symbols of the German city of Ravensburg.
E857536 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: Blaserturm | Statement: [Ravensburg, hasLandmark, Blaserturm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blaserturm
Context triple: [Ravensburg, hasLandmark, Blaserturm]
  • A. Roter Turm
    Roter Turm is a historic medieval tower and prominent architectural landmark in the city center of Chemnitz, Germany.
  • B. Roter Turm
    Roter Turm is a historic clock and bell tower in Halle (Saale), Germany, and one of the city’s most recognizable architectural landmarks.
  • C. Pulverturm
    Pulverturm is a historic defensive tower that forms part of the medieval Musegg Wall fortifications in Lucerne, Switzerland.
  • D. Schmalzturm
    Schmalzturm is a historic medieval tower and notable architectural landmark in the Bavarian town of Weißenburg in Bayern, Germany.
  • E. Schmalzturm
    Schmalzturm is a historic medieval tower in the Bavarian town of Landsberg am Lech, notable as a landmark of its old town fortifications.
  • 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: Blaserturm
Triple: [Ravensburg, hasLandmark, Blaserturm]
Generated description
Blaserturm is a historic medieval watch and bell tower that serves as one of the most recognizable symbols of the German city of Ravensburg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Blaserturm
Target entity description: Blaserturm is a historic medieval watch and bell tower that serves as one of the most recognizable symbols of the German city of Ravensburg.
  • A. Roter Turm
    Roter Turm is a historic medieval tower and prominent architectural landmark in the city center of Chemnitz, Germany.
  • B. Roter Turm
    Roter Turm is a historic clock and bell tower in Halle (Saale), Germany, and one of the city’s most recognizable architectural landmarks.
  • C. Pulverturm
    Pulverturm is a historic defensive tower that forms part of the medieval Musegg Wall fortifications in Lucerne, Switzerland.
  • D. Schmalzturm
    Schmalzturm is a historic medieval tower and notable architectural landmark in the Bavarian town of Weißenburg in Bayern, Germany.
  • E. Schmalzturm
    Schmalzturm is a historic medieval tower in the Bavarian town of Landsberg am Lech, notable as a landmark of its old town fortifications.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d309a4508190ad9de37171a64dba completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d75026fb0881908e4d16b3fde531c0 completed April 9, 2026, 7:07 a.m.
NEDg Description generation batch_69d7618b0f2481908149596dc86d4593 completed April 9, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_69d77015ae688190870976309e2b912b completed April 9, 2026, 9:23 a.m.
Created at: April 6, 2026, 11:46 a.m.