Triple
T19553674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trap Muzik |
E489253
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object | MJG |
—
|
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: MJG | Statement: [Trap Muzik, featuresArtist, MJG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MJG Context triple: [Trap Muzik, featuresArtist, MJG]
-
A.
MJG
chosen
MJG is an American rapper best known as one half of the influential Southern hip hop duo 8Ball & MJG.
-
B.
MJ
MJ is the widely used nickname for Michael Jordan, the legendary American basketball player often regarded as the greatest in NBA history.
-
C.
MJ
MJ is a reimagined version of the Mary Jane Watson character who appears as Peter Parker’s sharp, observant classmate and love interest in the Marvel Cinematic Universe Spider-Man films.
-
D.
MJ
MJ is a Master of Jurisprudence graduate law degree designed for non-lawyers seeking advanced legal knowledge in a specific field.
-
E.
MG
MG is a historic British automotive marque best known for its sports cars, now owned and produced by Chinese manufacturer SAIC Motor.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63d3254548190828a5f7e9a851ef8 |
completed | April 20, 2026, 2:50 p.m. |
Created at: April 10, 2026, 1:41 p.m.