Triple
T13278346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dillingen district |
E316249
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Lutzingen
Lutzingen is a small municipality in the Bavarian region of southern Germany, known for its rural character and location within the administrative district of Dillingen an der Donau.
|
E1042356
|
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: Lutzingen | Statement: [Dillingen district, containsMunicipality, Lutzingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lutzingen Context triple: [Dillingen district, containsMunicipality, Lutzingen]
-
A.
Lüsslingen
Lüsslingen is a village and former municipality in the canton of Solothurn in Switzerland.
-
B.
Küssnacht
Küssnacht is a picturesque Swiss municipality in the canton of Schwyz, known for its lakeside setting, historic village center, and association with the William Tell legend.
-
C.
Steißlingen
Steißlingen is a municipality in the district of Konstanz in the state of Baden-Württemberg in southern Germany.
-
D.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
-
E.
Niederbühl
Niederbühl is a district of the town of Rastatt in the state of Baden-Württemberg in southwestern Germany.
- 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: Lutzingen Triple: [Dillingen district, containsMunicipality, Lutzingen]
Generated description
Lutzingen is a small municipality in the Bavarian region of southern Germany, known for its rural character and location within the administrative district of Dillingen an der Donau.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lutzingen Target entity description: Lutzingen is a small municipality in the Bavarian region of southern Germany, known for its rural character and location within the administrative district of Dillingen an der Donau.
-
A.
Lüsslingen
Lüsslingen is a village and former municipality in the canton of Solothurn in Switzerland.
-
B.
Küssnacht
Küssnacht is a picturesque Swiss municipality in the canton of Schwyz, known for its lakeside setting, historic village center, and association with the William Tell legend.
-
C.
Steißlingen
Steißlingen is a municipality in the district of Konstanz in the state of Baden-Württemberg in southern Germany.
-
D.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
-
E.
Niederbühl
Niederbühl is a district of the town of Rastatt in the state of Baden-Württemberg in southwestern Germany.
- 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99043fba88190872ede6f63e2fbcb |
completed | April 11, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f74610b2c481909497296e999226e8 |
completed | May 3, 2026, 12:56 p.m. |
| NEDg | Description generation | batch_69f74b744de88190b0d9dad1c91b11af |
completed | May 3, 2026, 1:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f74befe7008190a059c8ec7b25f134 |
completed | May 3, 2026, 1:21 p.m. |
Created at: April 9, 2026, 9:26 p.m.