Triple
T20128534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pamela Franklin |
E490822
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Pamela Franklin |
—
|
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: Pamela Franklin | Statement: [Pamela Franklin, name, Pamela Franklin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pamela Franklin Context triple: [Pamela Franklin, name, Pamela Franklin]
-
A.
Pamela Franklin
chosen
Pamela Franklin is a British actress best known for her work as a child and young adult in 1960s and 1970s films and television, particularly in psychological horror and drama.
-
B.
Pamela Frank
Pamela Frank is an acclaimed American violinist renowned for her expressive performances and influential teaching career.
-
C.
Pamela Frank
Pamela Frank is the second wife of singer and civil rights activist Harry Belafonte, known primarily for her long-term marriage to the entertainer.
-
D.
Pamela Jenkins
Pamela Jenkins is a fictional character from the Saw horror film franchise, appearing in the movie "Saw VI."
-
E.
Paula Ellis
Paula Ellis is known as the former wife of acclaimed American actor Rod Steiger.
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6675fe3d48190b0c20b483a951e68 |
completed | April 20, 2026, 5:50 p.m. |
Created at: April 11, 2026, 11:31 p.m.