Triple
T20645604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Station Agent |
E507346
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Patricia Clarkson |
—
|
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: Patricia Clarkson | Statement: [The Station Agent, starring, Patricia Clarkson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Patricia Clarkson Context triple: [The Station Agent, starring, Patricia Clarkson]
-
A.
Patricia Clarkson
chosen
Patricia Clarkson is an American actress acclaimed for her versatile performances in film, television, and theater, often in complex supporting roles.
-
B.
Mary Bellingham
Mary Bellingham was the wife of John Bellingham, the man infamous for assassinating British Prime Minister Spencer Perceval in 1812.
-
C.
Anne Rennie
Anne Rennie is known as the wife of bestselling adventure novelist Wilbur Smith.
-
D.
Marsha Mason
Marsha Mason is an American actress known for her acclaimed film and stage work, including multiple Academy Award–nominated performances in 1970s and 1980s dramas and romantic comedies.
-
E.
Catherine Craig
Catherine Craig was an American film actress active in the 1940s, known for her supporting roles in Hollywood productions.
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1dd79481909de985d03ab861c2 |
completed | April 20, 2026, 10:56 p.m. |
Created at: April 16, 2026, 11:43 a.m.