Triple
T22150100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I'll Be Around |
E547389
|
entity |
| Predicate | hasPerformer |
P5936
|
FINISHED |
| Object | Tony Desare |
—
|
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: Tony Desare | Statement: [I'll Be Around, hasPerformer, Tony Desare]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tony Desare Context triple: [I'll Be Around, hasPerformer, Tony Desare]
-
A.
Tony Desare
chosen
Tony DeSare is an American jazz and pop singer, pianist, and songwriter known for his stylish interpretations of standards and original compositions.
-
B.
Jon Caliri
Jon Caliri is an actor best known for playing the character Vinnie Pasetta.
-
C.
Matthew Shafer
Matthew Shafer is an American writer known for his work on the animated series "Cowboy Bebop" and related projects.
-
D.
Matthew Shafer
Matthew Shafer, better known by his stage name Uncle Kracker, is an American singer-songwriter and musician recognized for his blend of rock, country, and pop influences.
-
E.
Phil DeVoss
Phil DeVoss is a fictional character from the romantic comedy-drama film "Elizabethtown," which explores themes of family, failure, and self-discovery.
- 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_69e11e3b52088190ad5df386d01eb2fb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129f37dac8190a7cecb12f4271515 |
completed | April 28, 2026, 9:43 p.m. |
Created at: April 16, 2026, 8:33 p.m.