Triple
T20689263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frances Bavier |
E508504
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | 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: Bavier | Statement: [Frances Bavier, familyName, Bavier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bavier Context triple: [Frances Bavier, familyName, Bavier]
-
A.
Bavier
chosen
Bavier is the surname of Frances Bavier, the American actress best known for playing Aunt Bee on the classic television series "The Andy Griffith Show."
-
B.
Baier
Baier is a surname most prominently associated with Bret Baier, the American television news anchor and host on Fox News.
-
C.
Bochsa
Bochsa is the surname of Nicolas-Charles Bochsa, a 19th-century French composer, harpist, and influential music teacher.
-
D.
Starnberg
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
-
E.
Schwarzenberg
Schwarzenberg is the noble family name of a prominent Central European princely house historically influential in Austrian and Bohemian politics and military affairs.
- 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_69e0b4c1ed408190b72dd26b1e33f8a1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c10b7b808190bdb8b08e53168fb8 |
completed | April 21, 2026, 12:12 a.m. |
Created at: April 16, 2026, 11:56 a.m.