Triple
T4342567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weißenburg in Bayern |
E97816
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Schmalzturm
Schmalzturm is a historic medieval tower and notable architectural landmark in the Bavarian town of Weißenburg in Bayern, Germany.
|
E433933
|
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: Schmalzturm | Statement: [Weißenburg in Bayern, hasLandmark, Schmalzturm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schmalzturm Context triple: [Weißenburg in Bayern, hasLandmark, Schmalzturm]
-
A.
Schmalzturm
Schmalzturm is a historic medieval tower in the Bavarian town of Landsberg am Lech, notable as a landmark of its old town fortifications.
-
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.
Roter Turm
Roter Turm is a historic medieval tower and prominent architectural landmark in the city center of Chemnitz, Germany.
-
D.
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.
-
E.
Käfigturm
Käfigturm is a historic medieval tower and former city gate in Bern, Switzerland, now serving as a prominent landmark and cultural venue.
- 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: Schmalzturm Triple: [Weißenburg in Bayern, hasLandmark, Schmalzturm]
Generated description
Schmalzturm is a historic medieval tower and notable architectural landmark in the Bavarian town of Weißenburg in Bayern, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schmalzturm Target entity description: Schmalzturm is a historic medieval tower and notable architectural landmark in the Bavarian town of Weißenburg in Bayern, Germany.
-
A.
Schmalzturm
Schmalzturm is a historic medieval tower in the Bavarian town of Landsberg am Lech, notable as a landmark of its old town fortifications.
-
B.
Roter Turm
Roter Turm is a historic medieval tower and prominent architectural landmark in the city center of Chemnitz, Germany.
-
C.
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.
-
D.
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.
-
E.
Käfigturm
Käfigturm is a historic medieval tower and former city gate in Bern, Switzerland, now serving as a prominent landmark and cultural venue.
- 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_69b34548402c819085ab68b27c235a87 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351878c148190b384053479d41caf |
completed | March 12, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5dba2b49c81909b7bf87672d71611 |
completed | March 14, 2026, 10:05 p.m. |
| NEDg | Description generation | batch_69b5df98cf5481909dac60a952fab0a9 |
completed | March 14, 2026, 10:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5e01c65648190a34a86dd5a2c8fc8 |
completed | March 14, 2026, 10:24 p.m. |
Created at: March 12, 2026, 11:14 p.m.