Triple
T7507021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jos Wienen |
E177414
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Wienen
Wienen is a Dutch surname most notably borne by politician and mayor Jos Wienen.
|
E687907
|
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: Wienen | Statement: [Jos Wienen, familyName, Wienen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wienen Context triple: [Jos Wienen, familyName, Wienen]
-
A.
Wien
Wien is a German surname most notably borne by physicist Wilhelm Wien, known for his work on blackbody radiation and Wien's displacement law.
-
B.
Vienna
Vienna is the capital city of Austria, renowned for its rich imperial history, classical music heritage, and vibrant cultural and intellectual life.
-
C.
Vienna
Vienna is a suburban town in Fairfax County, Virginia, known for its residential neighborhoods, proximity to Washington, D.C., and access to the Washington Metro via the nearby Vienna/Fairfax–GMU station.
-
D.
Vienna
Vienna is a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
-
E.
Vienna
Vienna is the strong-willed saloon owner and central female protagonist in the 1954 Western film "Johnny Guitar."
- 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: Wienen Triple: [Jos Wienen, familyName, Wienen]
Generated description
Wienen is a Dutch surname most notably borne by politician and mayor Jos Wienen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wienen Target entity description: Wienen is a Dutch surname most notably borne by politician and mayor Jos Wienen.
-
A.
Wien
Wien is a German surname most notably borne by physicist Wilhelm Wien, known for his work on blackbody radiation and Wien's displacement law.
-
B.
Vienna
Vienna is the capital city of Austria, renowned for its rich imperial history, classical music heritage, and vibrant cultural and intellectual life.
-
C.
Vienna
Vienna is a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
-
D.
Vienna
Vienna is a suburban town in Fairfax County, Virginia, known for its residential neighborhoods, proximity to Washington, D.C., and access to the Washington Metro via the nearby Vienna/Fairfax–GMU station.
-
E.
Vienna
Vienna is the strong-willed saloon owner and central female protagonist in the 1954 Western film "Johnny Guitar."
- 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_69c69f276b108190af2cc790b6554544 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5b76a288190bb3608a5e3bfa212 |
completed | March 27, 2026, 9:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7b042c8819098e345be61bbe943 |
completed | March 29, 2026, 6:33 a.m. |
| NEDg | Description generation | batch_69c8c87bca908190a44e839824c23e95 |
completed | March 29, 2026, 6:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8c8e5e9f081908288b38ea25e81d2 |
completed | March 29, 2026, 6:38 a.m. |
Created at: March 27, 2026, 3:45 p.m.