Triple
T21378548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ralph Furley |
E527278
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object | Cindy Snow |
—
|
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: Cindy Snow | Statement: [Ralph Furley, associatedWithCharacter, Cindy Snow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cindy Snow Context triple: [Ralph Furley, associatedWithCharacter, Cindy Snow]
-
A.
Cindy Snow
chosen
Cindy Snow is a bubbly, somewhat naive nurse who serves as one of the central roommates on the classic American sitcom "Three's Company."
-
B.
Tina Snow
Tina Snow is an alter ego and early mixtape title of American rapper Megan Thee Stallion, embodying her confident, hardcore Southern rap persona.
-
C.
Cindy Green
Cindy Green is a central character in the fantasy drama film "The Odd Life of Timothy Green," portrayed as a hopeful, loving woman who longs to become a mother.
-
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 Holland
Cindy Holland is a television executive best known for her influential role in developing and overseeing original content at Netflix.
- 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0cb138081909bcbf295483656cb |
completed | April 22, 2026, 11:28 a.m. |
Created at: April 16, 2026, 5:11 p.m.