Triple
T13021423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smile Please |
E326179
|
entity |
| Predicate | performer |
P1363
|
FINISHED |
| Object | Deniece Williams |
E975893
|
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: Deniece Williams | Statement: [Smile Please, performer, Deniece Williams]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deniece Williams Context triple: [Smile Please, performer, Deniece Williams]
-
A.
Deniece Williams
chosen
Deniece Williams is an American soul and R&B singer best known for her powerful four-octave range and hits like "Let's Hear It for the Boy."
-
B.
Cheryl Lynn
Cheryl Lynn is an American R&B and disco singer best known for her 1978 hit single "Got to Be Real."
-
C.
Diane Caesar
Diane Caesar is known as the wife of the late American actor and voice-over artist Adolph Caesar.
-
D.
Loleatta Holloway
Loleatta Holloway was an American soul and disco singer renowned for her powerful, gospel-infused vocals and influential dance-floor anthems like "Love Sensation."
-
E.
Kasie Hines
Kasie Hines is a forensic scientist character on the television series "NCIS," where she works alongside medical examiner Jimmy Palmer.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ecf21bc819082fb512bc479b4be |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbcb86148190ad1b19c6e8764397 |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:52 p.m.