Triple
T15947601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lauingen |
E386724
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Schimmelturm
Schimmelturm is a historic tower and prominent architectural landmark in the Bavarian town of Lauingen, Germany.
|
E1184328
|
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: Schimmelturm | Statement: [Lauingen, hasLandmark, Schimmelturm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schimmelturm Context triple: [Lauingen, hasLandmark, Schimmelturm]
-
A.
Schirmerturm
Schirmerturm is one of the historic defensive towers incorporated into Lucerne’s medieval Musegg Wall fortifications in Switzerland.
-
B.
Schmalzturm
Schmalzturm is a historic medieval tower and notable architectural landmark in the Bavarian town of Weißenburg in Bayern, Germany.
-
C.
Schmalzturm
Schmalzturm is a historic medieval tower in the Bavarian town of Landsberg am Lech, notable as a landmark of its old town fortifications.
-
D.
Pulverturm
Pulverturm is a historic defensive tower that forms part of the medieval Musegg Wall fortifications in Lucerne, Switzerland.
-
E.
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.
- 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: Schimmelturm Triple: [Lauingen, hasLandmark, Schimmelturm]
Generated description
Schimmelturm is a historic tower and prominent architectural landmark in the Bavarian town of Lauingen, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schimmelturm Target entity description: Schimmelturm is a historic tower and prominent architectural landmark in the Bavarian town of Lauingen, Germany.
-
A.
Schirmerturm
Schirmerturm is one of the historic defensive towers incorporated into Lucerne’s medieval Musegg Wall fortifications in Switzerland.
-
B.
Schmalzturm
Schmalzturm is a historic medieval tower and notable architectural landmark in the Bavarian town of Weißenburg in Bayern, Germany.
-
C.
Schmalzturm
Schmalzturm is a historic medieval tower in the Bavarian town of Landsberg am Lech, notable as a landmark of its old town fortifications.
-
D.
Pulverturm
Pulverturm is a historic defensive tower that forms part of the medieval Musegg Wall fortifications in Lucerne, Switzerland.
-
E.
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.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156d2fda8819085279d2a0f8a02ab |
completed | April 16, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5c0c8a481908aa7a40bca15e38e |
completed | May 9, 2026, 10:31 p.m. |
| NEDg | Description generation | batch_69ffb6d3bc6c81909e4bbedeea557615 |
completed | May 9, 2026, 10:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb7364cf88190b0930af7768dc429 |
completed | May 9, 2026, 10:37 p.m. |
Created at: April 10, 2026, 4:53 a.m.