Triple
T13891279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dom Kennedy |
E333974
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object |
Skeme
Skeme is a Los Angeles-based rapper known for his West Coast sound and collaborations with prominent hip-hop artists.
|
E1068962
|
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: Skeme | Statement: [Dom Kennedy, associatedAct, Skeme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skeme Context triple: [Dom Kennedy, associatedAct, Skeme]
-
A.
Chez Scheme
Chez Scheme is a high-performance, optimizing implementation of the Scheme programming language widely used for both research and production systems.
-
B.
Sikma
Sikma is a surname most notably associated with Jack Sikma, a Hall of Fame American basketball player known for his successful NBA career with the Seattle SuperSonics.
-
C.
Cypher
Cypher is a 2002 science fiction thriller film directed by Vincenzo Natali that explores corporate espionage, identity, and memory manipulation.
-
D.
Cypher
Cypher is a Marvel Comics mutant best known for his extraordinary ability to intuitively understand and translate any language, including spoken, written, and even computer or body language.
-
E.
Labda
Labda is a figure in ancient Greek history and mythology known primarily as the mother of Cypselus, the first tyrant of Corinth.
- 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: Skeme Triple: [Dom Kennedy, associatedAct, Skeme]
Generated description
Skeme is a Los Angeles-based rapper known for his West Coast sound and collaborations with prominent hip-hop artists.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Skeme Target entity description: Skeme is a Los Angeles-based rapper known for his West Coast sound and collaborations with prominent hip-hop artists.
-
A.
Chez Scheme
Chez Scheme is a high-performance, optimizing implementation of the Scheme programming language widely used for both research and production systems.
-
B.
Sikma
Sikma is a surname most notably associated with Jack Sikma, a Hall of Fame American basketball player known for his successful NBA career with the Seattle SuperSonics.
-
C.
Cypher
Cypher is a 2002 science fiction thriller film directed by Vincenzo Natali that explores corporate espionage, identity, and memory manipulation.
-
D.
Cypher
Cypher is a Marvel Comics mutant best known for his extraordinary ability to intuitively understand and translate any language, including spoken, written, and even computer or body language.
-
E.
Labda
Labda is a figure in ancient Greek history and mythology known primarily as the mother of Cypselus, the first tyrant of Corinth.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a3a24881908d81d634622fbbcc |
completed | April 14, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c71a43908190bc7537f0a2379599 |
completed | May 3, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69f7c8d477f881908f8cfd2783e7f10f |
completed | May 3, 2026, 10:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7ca27ffd4819080bccd6bfd88ddb3 |
completed | May 3, 2026, 10:20 p.m. |
Created at: April 9, 2026, 10:15 p.m.