Triple
T17460836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Had Enough |
E425146
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Slim Jxmmi |
—
|
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: Slim Jxmmi | Statement: [Had Enough, writer, Slim Jxmmi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Slim Jxmmi Context triple: [Had Enough, writer, Slim Jxmmi]
-
A.
Slim Jxmmi
chosen
Slim Jxmmi is an American rapper best known as one half of the hip hop duo Rae Sremmurd.
-
B.
SLIM
SLIM is a Japanese lunar lander mission developed by JAXA to demonstrate high-precision, lightweight Moon-landing technology.
-
C.
Slim
Slim is the surname of Bill Slim, a prominent British field marshal who played a key leadership role in the Burma Campaign during World War II.
-
D.
Slim
Slim is a given name or nickname commonly used for people with a slender build or as a casual moniker in various English-speaking cultures.
-
E.
Slim
Slim is a lightweight Ruby templating engine known for its minimal syntax and fast rendering performance.
- 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451a3031c8190ab1dd0d41b002dd2 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.