Triple
T15948609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hendrik Tennekes |
E386753
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Tennekes
Tennekes is a Dutch surname most notably associated with Hendrik Tennekes, a meteorologist and turbulence researcher.
|
E1184739
|
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: Tennekes | Statement: [Hendrik Tennekes, familyName, Tennekes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tennekes Context triple: [Hendrik Tennekes, familyName, Tennekes]
-
A.
Rik Van de Velde
Rik Van de Velde is a Belgian former professional cyclist known for competing in road racing events in the 1990s.
-
B.
Benno van den Berg
Benno van den Berg is a Dutch mathematician known for his work in category theory, logic, and the foundations of mathematics.
-
C.
Martin Louw
Martin Louw is a person bearing the surname Louw, which is associated with several notable individuals, though specific widely recognized achievements for this particular bearer are not clearly documented.
-
D.
Theo Scholten
Theo Scholten was a Dutch art patron and collector best known for establishing the sculpture-focused Museum Beelden aan Zee in Scheveningen.
-
E.
Ard Schenk
Ard Schenk is a Dutch former speed skater renowned as one of the sport’s all-time greats, particularly dominant in the early 1970s.
- 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: Tennekes Triple: [Hendrik Tennekes, familyName, Tennekes]
Generated description
Tennekes is a Dutch surname most notably associated with Hendrik Tennekes, a meteorologist and turbulence researcher.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tennekes Target entity description: Tennekes is a Dutch surname most notably associated with Hendrik Tennekes, a meteorologist and turbulence researcher.
-
A.
Rik Van de Velde
Rik Van de Velde is a Belgian former professional cyclist known for competing in road racing events in the 1990s.
-
B.
Benno van den Berg
Benno van den Berg is a Dutch mathematician known for his work in category theory, logic, and the foundations of mathematics.
-
C.
Martin Louw
Martin Louw is a person bearing the surname Louw, which is associated with several notable individuals, though specific widely recognized achievements for this particular bearer are not clearly documented.
-
D.
Theo Scholten
Theo Scholten was a Dutch art patron and collector best known for establishing the sculpture-focused Museum Beelden aan Zee in Scheveningen.
-
E.
Ard Schenk
Ard Schenk is a Dutch former speed skater renowned as one of the sport’s all-time greats, particularly dominant in the early 1970s.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156d3cc04819097367369a78d6ef2 |
completed | April 16, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5c207588190a3d17e5f09d12997 |
completed | May 9, 2026, 10:31 p.m. |
| NEDg | Description generation | batch_69ffb706eb348190baba254656fc0e71 |
completed | May 9, 2026, 10:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb7812bf08190918c1410565633e2 |
completed | May 9, 2026, 10:38 p.m. |
Created at: April 10, 2026, 4:53 a.m.