Triple
T13792610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Way 2 Fonky |
E331435
|
entity |
| Predicate | followedBy |
P78
|
FINISHED |
| Object | Safe + Sound |
E331436
|
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: Safe + Sound | Statement: [Way 2 Fonky, followedBy, Safe + Sound]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Safe + Sound Context triple: [Way 2 Fonky, followedBy, Safe + Sound]
-
A.
Safe + Sound
chosen
Safe + Sound is a 1995 West Coast hip hop album by DJ Quik that showcases his signature G-funk production and laid-back, funk-infused style.
-
B.
Safe and Sound
"Safe and Sound" is a song by American country duo Florida Georgia Line from their album "Anything Goes."
-
C.
The Sound Factory
The Sound Factory is a renowned Los Angeles recording studio known for hosting sessions by prominent jazz and rock artists, including Charles Mingus.
-
D.
Soundgasm
Soundgasm is a popular Afrobeats song by Nigerian artist Rema, known for its sensual lyrics and smooth, melodic production.
-
E.
Safe from Harm
"Safe from Harm" is a 1990 trip-hop track by Massive Attack, known for its dark, atmospheric production and soulful vocals that helped define the group's early sound.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0258a1408190a837d17c6d6a2bd4 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b0817bd88190a46e539f2ff24d83 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:11 p.m.