Triple
T17444152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dixie Griffith |
E424735
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Cindi Knight |
—
|
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: Cindi Knight | Statement: [Dixie Griffith, relative, Cindi Knight]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cindi Knight Context triple: [Dixie Griffith, relative, Cindi Knight]
-
A.
Cindi Knight
chosen
Cindi Knight is an American actress best known as the third wife of television icon Andy Griffith.
-
B.
Cindy Henderson
Cindy Henderson is an actress best known for voicing Wednesday Addams in the 1970s animated adaptation of The Addams Family.
-
C.
Cindy Holland
Cindy Holland is a television executive best known for her influential role in developing and overseeing original content at Netflix.
-
D.
Cindy Morgan
Cindy Morgan is an American actress best known for her roles in the comedy film "Caddyshack" and the science fiction film "Tron."
-
E.
Cindy Sanders
Cindy Sanders is a popular, kind-hearted cheerleader and classmate in the TV series "Freaks and Geeks," known as the crush of main character Sam Weir.
- 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44ffa2d84819086474649eba1065c |
completed | April 19, 2026, 3:46 a.m. |
Created at: April 10, 2026, 5:47 a.m.