Triple
T19781954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quiz Show |
E475155
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Mira Sorvino |
—
|
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: Mira Sorvino | Statement: [Quiz Show, stars, Mira Sorvino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mira Sorvino Context triple: [Quiz Show, stars, Mira Sorvino]
-
A.
Mira Sorvino
chosen
Mira Sorvino is an American actress and Academy Award winner known for her versatile performances in film and television.
-
B.
Marisa Tomei
Marisa Tomei is an Academy Award–winning American actress known for her versatile film and television roles, including portraying Aunt May in the Marvel Cinematic Universe.
-
C.
Annabella Sciorra
Annabella Sciorra is an American actress known for her work in film and television, including acclaimed roles in movies like "Jungle Fever" and the TV series "The Sopranos."
-
D.
Lorraine Bracco
Lorraine Bracco is an American actress best known for her roles in the film "Goodfellas" and the television series "The Sopranos."
-
E.
Téa Leoni
Téa Leoni is an American actress and producer best known for her leading roles in film and television, including the political drama series "Madam Secretary."
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653846a248190adc4afe0dc29a402 |
completed | April 20, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:49 p.m.