Triple
T13735799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ooh I Love You Rakeem |
E329941
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Prince Rakeem |
E65368
|
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: Prince Rakeem | Statement: [Ooh I Love You Rakeem, producer, Prince Rakeem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prince Rakeem Context triple: [Ooh I Love You Rakeem, producer, Prince Rakeem]
-
A.
Prince Rakeem
chosen
Prince Rakeem is an early stage name of RZA, the influential producer, rapper, and de facto leader of the Wu-Tang Clan.
-
B.
Prince Akeem Joffer
Prince Akeem Joffer is the idealistic and charming crown prince of the fictional African nation of Zamunda in the comedy film "Coming to America."
-
C.
Rakeem Calief Myer
Rakeem Calief Myer is an American rapper and producer better known by his stage name Roc Marciano, noted for his influential role in underground hip-hop.
-
D.
Raheem
Raheem is a central fictional protagonist known for his role as the main character in the story "Juice."
-
E.
Raheem
Raheem is an American rapper best known as an early member of the influential Houston hip hop group the Geto Boys.
- 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_69d80772315881908f980cae40d91664 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de020351fc8190a554a48c552e83b5 |
completed | April 14, 2026, 8:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1b661e4819087bac0cd84489baa |
completed | May 6, 2026, 8:16 p.m. |
Created at: April 9, 2026, 9:55 p.m.