Triple
T12202535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Be Faithful |
E290752
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object | Fatman Scoop |
E59227
|
NE FINISHED |
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: Fatman Scoop | Statement: [Be Faithful, featuresArtist, Fatman Scoop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fatman Scoop Context triple: [Be Faithful, featuresArtist, Fatman Scoop]
-
A.
Fatman Scoop
chosen
Fatman Scoop is an American hype man, rapper, and radio personality best known for his booming voice and energetic club anthems like the hit single "Be Faithful."
-
B.
Fatman
Fatman is a darkly comedic action film in which Mel Gibson portrays a gritty, world-weary Santa Claus targeted by an assassin.
-
C.
Fat Mac
Fat Mac is the popular nickname for Apple's Macintosh 512K, an early 1980s personal computer notable for its increased memory over the original Macintosh.
-
D.
Phat Farm
Phat Farm is a pioneering urban fashion and lifestyle brand that helped popularize hip-hop-influenced streetwear in mainstream American culture.
-
E.
Fat Man’s Squeeze
Fat Man’s Squeeze is a narrow, winding rock passageway and popular photo-op attraction within Rock City Gardens on Lookout Mountain in Georgia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c7b97408190a11ea37cc6edf18c |
completed | April 10, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63ee694848190a1362934110b6ceb |
completed | May 2, 2026, 6:13 p.m. |
Created at: April 8, 2026, 9:51 p.m.