Triple
T12621208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hebbel Prize |
E301382
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object |
Wesselburen
Wesselburen is a small town in the Dithmarschen district of Schleswig-Holstein, Germany, known as the birthplace of poet Friedrich Hebbel and for its cultural heritage.
|
E1001506
|
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: Wesselburen | Statement: [Hebbel Prize, location, Wesselburen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wesselburen Context triple: [Hebbel Prize, location, Wesselburen]
-
A.
Blankenburg
Blankenburg is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and village-like atmosphere.
-
B.
Blankenburg
Blankenburg is a town in central Germany, located in the Harz region of the state of Saxony-Anhalt.
-
C.
Zwanenburg
Zwanenburg is a village in North Holland, Netherlands, situated near Amsterdam and known as a suburban residential community within the Haarlemmermeer municipality.
-
D.
Valkenburg
Valkenburg is a village in the Dutch province of South Holland, known for its historic charm and proximity to the North Sea coast.
-
E.
Rozenburg
Rozenburg is a village in the municipality of Haarlemmermeer in the province of North Holland, Netherlands.
- 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: Wesselburen Triple: [Hebbel Prize, location, Wesselburen]
Generated description
Wesselburen is a small town in the Dithmarschen district of Schleswig-Holstein, Germany, known as the birthplace of poet Friedrich Hebbel and for its cultural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wesselburen Target entity description: Wesselburen is a small town in the Dithmarschen district of Schleswig-Holstein, Germany, known as the birthplace of poet Friedrich Hebbel and for its cultural heritage.
-
A.
Blankenburg
Blankenburg is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and village-like atmosphere.
-
B.
Blankenburg
Blankenburg is a town in central Germany, located in the Harz region of the state of Saxony-Anhalt.
-
C.
Zwanenburg
Zwanenburg is a village in North Holland, Netherlands, situated near Amsterdam and known as a suburban residential community within the Haarlemmermeer municipality.
-
D.
Valkenburg
Valkenburg is a village in the Dutch province of South Holland, known for its historic charm and proximity to the North Sea coast.
-
E.
Rozenburg
Rozenburg is a village in the municipality of Haarlemmermeer in the province of North Holland, Netherlands.
- 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d960c8671881909a102d28b0e7f603 |
completed | April 10, 2026, 8:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684daedc88190adc403f27a850b7a |
completed | May 2, 2026, 11:12 p.m. |
| NEDg | Description generation | batch_69f685dac5cc8190b4bc2d81186c9266 |
completed | May 2, 2026, 11:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6869156048190b548ecd04561deb8 |
completed | May 2, 2026, 11:19 p.m. |
Created at: April 9, 2026, 5:13 p.m.