Triple
T10587216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kulmbach district |
E249884
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Thurnau
Thurnau is a market town in northern Bavaria, Germany, known for its historic castle and traditional Franconian architecture.
|
E872636
|
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: Thurnau | Statement: [Kulmbach district, hasMunicipality, Thurnau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thurnau Context triple: [Kulmbach district, hasMunicipality, Thurnau]
-
A.
Flumenthal
Flumenthal is a municipality in the canton of Solothurn in northwestern Switzerland.
-
B.
Brannenburg
Brannenburg is a Bavarian municipality in southern Germany, known for its scenic Alpine setting and outdoor recreation opportunities.
-
C.
Wilhering
Wilhering is a municipality in Upper Austria, known for the historic Wilhering Abbey and its location near the city of Linz.
-
D.
Naunhof
Naunhof is a small town in the Free State of Saxony in eastern Germany, known for its surrounding lakes and forests near the city of Leipzig.
-
E.
Tureberg
Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
- 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: Thurnau Triple: [Kulmbach district, hasMunicipality, Thurnau]
Generated description
Thurnau is a market town in northern Bavaria, Germany, known for its historic castle and traditional Franconian architecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thurnau Target entity description: Thurnau is a market town in northern Bavaria, Germany, known for its historic castle and traditional Franconian architecture.
-
A.
Flumenthal
Flumenthal is a municipality in the canton of Solothurn in northwestern Switzerland.
-
B.
Brannenburg
Brannenburg is a Bavarian municipality in southern Germany, known for its scenic Alpine setting and outdoor recreation opportunities.
-
C.
Wilhering
Wilhering is a municipality in Upper Austria, known for the historic Wilhering Abbey and its location near the city of Linz.
-
D.
Naunhof
Naunhof is a small town in the Free State of Saxony in eastern Germany, known for its surrounding lakes and forests near the city of Leipzig.
-
E.
Tureberg
Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5276b0ae48190b2935230363239e0 |
completed | April 7, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b8b1b708190865e428128f98720 |
completed | April 10, 2026, 7:12 p.m. |
| NEDg | Description generation | batch_69d94d68f39c8190bc7ea90237a5bf5f |
completed | April 10, 2026, 7:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d9522d68b88190a63acb6d657168b4 |
completed | April 10, 2026, 7:40 p.m. |
Created at: April 6, 2026, 12:39 p.m.