Triple
T517276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stevie Wonder |
E10734
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Prince |
E43685
|
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 | Statement: [Stevie Wonder, influenced, Prince]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prince Context triple: [Stevie Wonder, influenced, Prince]
-
A.
Prince
chosen
Prince was an innovative American singer, songwriter, multi-instrumentalist, and producer known for his eclectic musical style, flamboyant stage presence, and profound influence on pop, funk, rock, and R&B music.
-
B.
King
The King is the reigning male monarch who serves as the head of state of the United Kingdom within its constitutional monarchy system.
-
C.
King
King is a common English surname borne by numerous notable figures, including civil rights leader Martin Luther King Jr.
-
D.
Jonathan King
Jonathan King is a British singer-songwriter, record producer, and former music industry figure known for his 1960s pop hits and later controversial legal troubles.
-
E.
DiDi Richards
DiDi Richards is an American professional basketball player and standout defensive guard who rose to prominence starring for the Baylor Lady Bears in college.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f19d81d48190bd65a02059fc8473 |
completed | Feb. 28, 2026, 1:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4a42b9a648190ab38c181da2ae0f6 |
completed | March 1, 2026, 8:40 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.