Triple
T17402932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beatrice Taylor |
E423140
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Frances Bavier |
—
|
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: Frances Bavier | Statement: [Beatrice Taylor, portrayedBy, Frances Bavier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frances Bavier Context triple: [Beatrice Taylor, portrayedBy, Frances Bavier]
-
A.
Frances Bavier
chosen
Frances Bavier was an American actress best known for her portrayal of the warm but no-nonsense Aunt Bee on the classic television sitcom "The Andy Griffith Show."
-
B.
Lucille Bliss
Lucille Bliss was an American voice actress best known for her work in classic animated films and television, including early Disney productions and the original Smurfs series.
-
C.
Fay Baker
Fay Baker was an American actress known for her character roles in mid-20th-century film and television, often appearing in dramas and thrillers.
-
D.
Marguerite Lauer
Marguerite Lauer was the wife of renowned French Egyptologist Jean-Philippe Lauer.
-
E.
Myrna Fahey
Myrna Fahey was an American actress known for her film and television roles in the 1950s and 1960s, often appearing in comedies and dramas.
- 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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b051cc48190872278ee0b52240d |
completed | April 19, 2026, 2:16 a.m. |
Created at: April 10, 2026, 5:45 a.m.