Triple
T7160573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenny Everett |
E166930
|
entity |
| Predicate | notableCharacter |
P1481
|
FINISHED |
| Object |
Marcel Wave
Marcel Wave is a flamboyant, camp hairdresser character created and performed by British comedian and DJ Kenny Everett on his television shows.
|
E645847
|
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: Marcel Wave | Statement: [Kenny Everett, notableCharacter, Marcel Wave]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marcel Wave Context triple: [Kenny Everett, notableCharacter, Marcel Wave]
-
A.
Nova Wav
Nova Wav is a Grammy-winning American songwriting and production duo known for crafting R&B and pop hits for major artists like Beyoncé.
-
B.
My Wave
"My Wave" is a song by the American rock band Soundgarden from their 1994 album *Superunknown*, showcasing their heavy, experimental grunge sound and unusual time signatures.
-
C.
Wellen
Wellen is a municipality in the Belgian province of Limburg, known for its rural character and fruit-growing landscape.
-
D.
The Perfect Wave
The Perfect Wave is a faith-based drama film that tells the true story of a young surfer’s spiritual awakening after a near-death experience.
-
E.
Waves
The Waves is the nickname for the athletic teams that represent Pepperdine University in intercollegiate sports.
- 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: Marcel Wave Triple: [Kenny Everett, notableCharacter, Marcel Wave]
Generated description
Marcel Wave is a flamboyant, camp hairdresser character created and performed by British comedian and DJ Kenny Everett on his television shows.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marcel Wave Target entity description: Marcel Wave is a flamboyant, camp hairdresser character created and performed by British comedian and DJ Kenny Everett on his television shows.
-
A.
Nova Wav
Nova Wav is a Grammy-winning American songwriting and production duo known for crafting R&B and pop hits for major artists like Beyoncé.
-
B.
My Wave
"My Wave" is a song by the American rock band Soundgarden from their 1994 album *Superunknown*, showcasing their heavy, experimental grunge sound and unusual time signatures.
-
C.
Wellen
Wellen is a municipality in the Belgian province of Limburg, known for its rural character and fruit-growing landscape.
-
D.
The Perfect Wave
The Perfect Wave is a faith-based drama film that tells the true story of a young surfer’s spiritual awakening after a near-death experience.
-
E.
Waves
The Waves is the nickname for the athletic teams that represent Pepperdine University in intercollegiate sports.
- 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_69c68887a5cc8190bec0ea96227164f7 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e82ce770819081dccf7ffd50c2ab |
completed | March 27, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7adc08b688190a00024727542c8b9 |
completed | March 28, 2026, 10:30 a.m. |
| NEDg | Description generation | batch_69c7ae661f4481908ee489023af9603b |
completed | March 28, 2026, 10:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7aef767848190b7edf7a99e2e019d |
completed | March 28, 2026, 10:35 a.m. |
Created at: March 27, 2026, 2:47 p.m.