Triple
T20620879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Funny Farm |
E506693
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Madolyn Smith |
—
|
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: Madolyn Smith | Statement: [Funny Farm, starring, Madolyn Smith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madolyn Smith Context triple: [Funny Farm, starring, Madolyn Smith]
-
A.
Madolyn Smith
chosen
Madolyn Smith is an American actress best known for her film and television roles in the 1980s, including prominent performances in comedies and dramas.
-
B.
Madolyn Madden
Madolyn Madden is a central character in the crime thriller film "The Departed," serving as a psychiatrist entangled in the lives of both a mole in the police and an undercover cop.
-
C.
Thelma Todd
Thelma Todd was a popular American film actress and comedian of the late silent and early sound era, best known for her work in Hal Roach comedies and films with the Marx Brothers.
-
D.
Julie Monroe
Julie Monroe is a film editor known for her work on major motion pictures, including the financial drama "Wall Street: Money Never Sleeps."
-
E.
Maxine Fox
Maxine Fox is a fictional character from the British police drama series "Sirens."
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe19ca481908c896bec49a025cd |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:42 a.m.