Triple

T7468745
Position Surface form Disambiguated ID Type / Status
Subject Wels E176447 entity
Predicate hasLandmark P105 FINISHED
Object Ledererturm
Ledererturm is a historic medieval tower and notable architectural landmark located in the Austrian city of Wels.
E667257 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: Ledererturm | Statement: [Wels, hasLandmark, Ledererturm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ledererturm
Context triple: [Wels, hasLandmark, Ledererturm]
  • 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. Humberg Tower
    Humberg Tower is a historic observation tower on the Humberg hill near Kaiserslautern in Germany, known for its panoramic views over the surrounding Palatinate region.
  • 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: Ledererturm
Triple: [Wels, hasLandmark, Ledererturm]
Generated description
Ledererturm is a historic medieval tower and notable architectural landmark located in the Austrian city of Wels.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ledererturm
Target entity description: Ledererturm is a historic medieval tower and notable architectural landmark located in the Austrian city of Wels.
  • 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. Humberg Tower
    Humberg Tower is a historic observation tower on the Humberg hill near Kaiserslautern in Germany, known for its panoramic views over the surrounding Palatinate region.
  • 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_69c69f223fd88190b4c69b95d7cbeeda completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f3f6f23881908e3e80b0c7335a15 completed March 27, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83475392c8190a51d24e1530c0c83 completed March 28, 2026, 8:05 p.m.
NEDg Description generation batch_69c835ce5bbc8190b968535c16cfc660 completed March 28, 2026, 8:10 p.m.
NED2 Entity disambiguation (via description) batch_69c836a80eb081908b9937944fe18661 completed March 28, 2026, 8:14 p.m.
Created at: March 27, 2026, 3:40 p.m.