Triple
T17045968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mühlacker |
E413568
|
entity |
| Predicate | hasCityDistrict |
P2709
|
FINISHED |
| Object |
Enzberg
Enzberg is a district of the town of Mühlacker in the state of Baden-Württemberg, Germany.
|
E1248314
|
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: Enzberg | Statement: [Mühlacker, hasCityDistrict, Enzberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Enzberg Context triple: [Mühlacker, hasCityDistrict, Enzberg]
-
A.
Reisenberg
Reisenberg is a small municipality in Lower Austria’s Baden District, known for its rural character and proximity to Vienna.
-
B.
Eikenberg
Eikenberg is a well-known cobbled climb in the Flemish Ardennes, frequently featured in Belgian professional cycling races.
-
C.
Belpberg
Belpberg is a small former municipality in the canton of Bern, Switzerland, situated on a plateau above the Gürbetal valley and known for its rural, scenic landscape.
-
D.
Elsterberg
Elsterberg is a small town in the Vogtland region of Saxony, Germany, known for its historic castle ruins and scenic location along the White Elster River.
-
E.
Oxenberg
Oxenberg is a surname most prominently associated with actress Catherine Oxenberg, known for her role on the television series "Dynasty" and her ties to European royalty.
- 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: Enzberg Triple: [Mühlacker, hasCityDistrict, Enzberg]
Generated description
Enzberg is a district of the town of Mühlacker in the state of Baden-Württemberg, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Enzberg Target entity description: Enzberg is a district of the town of Mühlacker in the state of Baden-Württemberg, Germany.
-
A.
Reisenberg
Reisenberg is a small municipality in Lower Austria’s Baden District, known for its rural character and proximity to Vienna.
-
B.
Eikenberg
Eikenberg is a well-known cobbled climb in the Flemish Ardennes, frequently featured in Belgian professional cycling races.
-
C.
Belpberg
Belpberg is a small former municipality in the canton of Bern, Switzerland, situated on a plateau above the Gürbetal valley and known for its rural, scenic landscape.
-
D.
Elsterberg
Elsterberg is a small town in the Vogtland region of Saxony, Germany, known for its historic castle ruins and scenic location along the White Elster River.
-
E.
Oxenberg
Oxenberg is a surname most prominently associated with actress Catherine Oxenberg, known for her role on the television series "Dynasty" and her ties to European royalty.
- 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3da9d7e988190a5e3991c7123f9b0 |
completed | April 18, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01233cd3d48190b002951881ef670b |
completed | May 11, 2026, 12:30 a.m. |
| NEDg | Description generation | batch_6a0124f158a08190a803b37378a2c253 |
completed | May 11, 2026, 12:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a012569322081908b60694851d50e4b |
completed | May 11, 2026, 12:40 a.m. |
Created at: April 10, 2026, 5:33 a.m.