Triple
T20236798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jill Arlyn Oppenheim |
E498170
|
entity |
| Predicate | stageName |
P7872
|
FINISHED |
| Object | Jill St. John |
—
|
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: Jill St. John | Statement: [Jill Arlyn Oppenheim, stageName, Jill St. John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jill St. John Context triple: [Jill Arlyn Oppenheim, stageName, Jill St. John]
-
A.
Jill St. John
chosen
Jill St. John is an American actress best known for playing Bond girl Tiffany Case in the James Bond film "Diamonds Are Forever."
-
B.
Gaynor Faye
Gaynor Faye is a British actress and writer best known for her roles in popular UK television dramas and soaps such as Coronation Street and Emmerdale.
-
C.
Stefanie Powers
Stefanie Powers is an American actress best known for her role as Jennifer Hart in the television series "Hart to Hart."
-
D.
Lorraine Taylor
Lorraine Taylor is known as a former spouse of musician and bandleader Ike Turner, associated with his early personal life and career period.
-
E.
Lindsay Wagner
Lindsay Wagner is an American actress best known for her Emmy-winning role as Jaime Sommers in the television series "The Bionic Woman."
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6716a5af0819095ea419a4d1f0d1d |
completed | April 20, 2026, 6:33 p.m. |
Created at: April 11, 2026, 11:40 p.m.