Triple
T22535716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M.A.D.E. |
E557146
|
entity |
| Predicate | featuredArtist |
P997
|
FINISHED |
| Object | T.I. |
—
|
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: T.I. | Statement: [M.A.D.E., featuredArtist, T.I.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T.I. Context triple: [M.A.D.E., featuredArtist, T.I.]
-
A.
T.I.
chosen
T.I. is an American rapper, actor, and record executive known as a pioneer of trap music and for hits like "Whatever You Like" and "Live Your Life."
-
B.
Ludacris
Ludacris is an American rapper, actor, and entrepreneur known for his witty Southern hip hop style and roles in the Fast & Furious film franchise.
-
C.
T-Pain
T-Pain is an American singer, rapper, and producer known for popularizing the creative use of Auto-Tune in mainstream hip-hop and R&B music.
-
D.
50 Cent
50 Cent is an American rapper, actor, and entrepreneur known for his influential early-2000s hip-hop albums and his breakout debut "Get Rich or Die Tryin'."
-
E.
Tyga
Tyga is an American rapper and songwriter known for hits like "Rack City" and his association with the Young Money Entertainment label.
- 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15edad0248190b990ddffbc786e05 |
completed | April 29, 2026, 1:28 a.m. |
Created at: April 16, 2026, 8:51 p.m.