Triple
T12258332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don't Dull |
E292157
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Samklef
Samklef is a Nigerian music producer and artist known for crafting hit Afrobeat tracks for prominent performers in the 2010s.
|
E972939
|
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: Samklef | Statement: [Don't Dull, producer, Samklef]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samklef Context triple: [Don't Dull, producer, Samklef]
-
A.
Smekkleysa
Smekkleysa is an Icelandic independent record label and arts collective known for fostering influential alternative and experimental music acts.
-
B.
Klakah
Klakah is a town in East Java, Indonesia, situated close to Mount Lamongan and known for its surrounding volcanic lakes and agricultural landscape.
-
C.
Salekasa
Salekasa is a town in the Gondia district of Maharashtra, India.
-
D.
Klecko
Klecko is the surname of former American football defensive lineman Joe Klecko, best known for his standout career with the New York Jets as part of the “New York Sack Exchange.”
-
E.
Saulgrub
Saulgrub is a small Bavarian municipality in southern Germany, situated in the alpine foothills and known for its rural character and scenic surroundings.
- 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: Samklef Triple: [Don't Dull, producer, Samklef]
Generated description
Samklef is a Nigerian music producer and artist known for crafting hit Afrobeat tracks for prominent performers in the 2010s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Samklef Target entity description: Samklef is a Nigerian music producer and artist known for crafting hit Afrobeat tracks for prominent performers in the 2010s.
-
A.
Smekkleysa
Smekkleysa is an Icelandic independent record label and arts collective known for fostering influential alternative and experimental music acts.
-
B.
Klakah
Klakah is a town in East Java, Indonesia, situated close to Mount Lamongan and known for its surrounding volcanic lakes and agricultural landscape.
-
C.
Salekasa
Salekasa is a town in the Gondia district of Maharashtra, India.
-
D.
Klecko
Klecko is the surname of former American football defensive lineman Joe Klecko, best known for his standout career with the New York Jets as part of the “New York Sack Exchange.”
-
E.
Saulgrub
Saulgrub is a small Bavarian municipality in southern Germany, situated in the alpine foothills and known for its rural character and scenic surroundings.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91ccadc3c81908fe68adc3fdcc851 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60abfc8588190ab9300c6e5e59092 |
completed | May 2, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69f61a13fd1481908a06ca65b276e0e1 |
completed | May 2, 2026, 3:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f61ad2bd0c8190ada37bc1f8ae160f |
completed | May 2, 2026, 3:40 p.m. |
Created at: April 8, 2026, 9:52 p.m.