Triple
T20035867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DJ Paul |
E497259
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Crunchy Black |
—
|
NE NERFINISHED |
How this triple was built (2 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: Crunchy Black | Statement: [DJ Paul, associatedAct, Crunchy Black]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crunchy Black Context triple: [DJ Paul, associatedAct, Crunchy Black]
-
A.
Crunchy Black
chosen
Crunchy Black is an American rapper and hypeman best known as a founding member of the Memphis hip hop group Three 6 Mafia.
-
B.
Golden Crisp
Golden Crisp is a sweet, puffed wheat breakfast cereal known for its honey-like flavor and long-time cartoon mascot Sugar Bear.
-
C.
Crunch
Crunch is a professional ice hockey team based in Syracuse, New York, competing in the American Hockey League as an affiliate of the NHL's Tampa Bay Lightning.
-
D.
Caramelo
"Caramelo" is a popular reggaeton/Latin urban hit song by Puerto Rican singer Ozuna, known for its catchy melody and romantic lyrics.
-
E.
Caramelo
Caramelo is a novel by Sandra Cisneros that explores a Mexican American family’s history, identity, and intergenerational relationships through the memories tied to a cherished rebozo (shawl).
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662e8573081909f71fda640aa3220 |
completed | April 20, 2026, 5:31 p.m. |
Created at: April 11, 2026, 3:36 p.m.