Triple
T555111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Look to You |
E11925
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Akon |
E60665
|
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: Akon | Statement: [I Look to You, producer, Akon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akon Context triple: [I Look to You, producer, Akon]
-
A.
Akon
chosen
Akon is a Senegalese-American singer, songwriter, and producer known for his distinctive R&B and hip-hop hits and numerous high-profile collaborations in the 2000s.
-
B.
Wyclef Jean
Wyclef Jean is a Haitian-born rapper, musician, and producer best known as a member of the Fugees and for his successful solo career blending hip hop, reggae, and world music.
-
C.
Chamillionaire
Chamillionaire is an American rapper and entrepreneur best known for his Grammy-winning hit "Ridin'" and his influential role in the mid-2000s Southern hip hop scene.
-
D.
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.
-
E.
Lupe Fiasco
Lupe Fiasco is an American rapper, songwriter, and producer known for his socially conscious lyrics and critically acclaimed albums such as "Food & Liquor" and "The Cool."
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4991dd7008190a6c1bc8bc832456d |
completed | March 1, 2026, 7:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5dc8df9708190976967ad4e45a597 |
completed | March 2, 2026, 6:53 p.m. |
Created at: March 1, 2026, 7:32 p.m.