Triple
T16468161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip Lawrence |
E399986
|
entity |
| Predicate | producerOf |
P490
|
FINISHED |
| Object | 24K Magic |
E329493
|
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: 24K Magic | Statement: [Philip Lawrence, producerOf, 24K Magic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 24K Magic Context triple: [Philip Lawrence, producerOf, 24K Magic]
-
A.
24K Magic
chosen
24K Magic is a funk- and R&B-infused studio album by Bruno Mars known for its retro sound and hit singles like "24K Magic" and "That's What I Like."
-
B.
Revenge of the Dreamers
Revenge of the Dreamers is a collaborative compilation project showcasing artists from J. Cole’s Dreamville Records label.
-
C.
Hotline Bling
"Hotline Bling" is a 2015 Drake hit single known for its minimalist production, viral music video, and widespread cultural impact.
-
D.
Get on Up
Get on Up is a 2014 biographical drama film about the life and career of soul music legend James Brown.
-
E.
Wyldstyle
Wyldstyle is a rebellious and resourceful Master Builder who plays a leading role in The Lego Movie’s fight against conformity and tyranny.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32dce342081909cad56dc92de13a2 |
completed | April 18, 2026, 7:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00581a11e881908681f68c26ee6a05 |
completed | May 10, 2026, 10:04 a.m. |
Created at: April 10, 2026, 5:11 a.m.