Triple
T21249338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kool G Rap |
E523697
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | 4,5,6 |
—
|
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: 4,5,6 | Statement: [Kool G Rap, notableWork, 4,5,6]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 4,5,6 Context triple: [Kool G Rap, notableWork, 4,5,6]
-
A.
4,5,6
chosen
4,5,6 is a 1995 studio album by Queens rapper Kool G Rap, noted for its gritty street narratives and influential role in mid-90s East Coast hip hop.
-
B.
4 3 2 1
4 3 2 1 is a novel by American author Paul Auster that explores themes of chance, identity, and storytelling through an experimental, metafictional narrative structure.
-
C.
3/6
3/6 is a battalion of the United States Marine Corps known for its infantry combat role and participation in major military operations.
-
D.
1-2-3
1-2-3 is a punk rock song by The Professionals, known for its driving energy and classic early-1980s UK punk sound.
-
E.
1-2-3
1-2-3 is a mid-1980s pop song by Miami Sound Machine that blends Latin rhythms with dance-pop and helped cement the group’s mainstream success.
- 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7359c7a648190b4345336ac3be024 |
completed | April 21, 2026, 8:30 a.m. |
Created at: April 16, 2026, 3:56 p.m.