Triple
T21449424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carole Bayer Sager |
E529168
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Carole |
—
|
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: Carole | Statement: [Carole Bayer Sager, givenName, Carole]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carole Context triple: [Carole Bayer Sager, givenName, Carole]
-
A.
Carole
chosen
Carole is a feminine given name of French origin, commonly used in English-speaking countries.
-
B.
Charlene
Charlene is a feminine given name derived from the male name Charles.
-
C.
Charlene
Charlene is a fictional character who works at the Metropolitan Public Library, often depicted as part of its staff in related stories.
-
D.
Charlene
"Charlene" is a soulful R&B ballad by Anthony Hamilton that became one of his signature songs, known for its heartfelt lyrics about love and regret.
-
E.
Carleen
Carleen is a small village in Cornwall, England, situated within the rural parish of Breage.
- 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9d11ca48190aafe25c97dfa5578 |
completed | April 23, 2026, 9:43 a.m. |
Created at: April 16, 2026, 6:06 p.m.