Triple
T5534429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carole Bayer Sager |
E145126
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Carole |
E209179
|
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: 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.
Carla
Carla is a feminine given name commonly used in various languages, often considered the female form of Carl or Charles.
-
D.
Carolyn
Carolyn Bessette-Kennedy was an American publicist and style icon best known as the wife of John F. Kennedy Jr.
-
E.
Barbara
Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
- 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_69c008f9955881909bfa8348b56b4739 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fa0141c81909a216be9f48d64e1 |
completed | March 22, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02810084c81909fde56d6ee4ad328 |
completed | March 22, 2026, 5:34 p.m. |
Created at: March 22, 2026, 3:34 p.m.