Triple
T21243142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Another Stakeout |
E523530
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Marcia Strassman |
—
|
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: Marcia Strassman | Statement: [Another Stakeout, starring, Marcia Strassman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marcia Strassman Context triple: [Another Stakeout, starring, Marcia Strassman]
-
A.
Marcia Strassman
chosen
Marcia Strassman was an American actress best known for her roles in the sitcom "Welcome Back, Kotter" and the "Honey, I Shrunk the Kids" film series.
-
B.
Roberta Seidman
Roberta Seidman was the wife of American actor John Garfield, a prominent film star of the 1930s and 1940s.
-
C.
Roberta Seidman
Roberta Seidman is known as the spouse of Julius Garfinkle.
-
D.
Joan E. Steinman
Joan E. Steinman is a legal scholar and professor known for her expertise in federal civil procedure and her authorship of leading treatises in the field.
-
E.
Gail Mutrux
Gail Mutrux is an American film producer known for her work on acclaimed dramas such as "News of the World" and "Donnie Brasco."
- 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_69e0b513b89c81908b27147e91368db2 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7352507448190ba1f14cef16d69be |
completed | April 21, 2026, 8:28 a.m. |
Created at: April 16, 2026, 3:47 p.m.