Triple
T20885101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swing Vote |
E514256
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Paula Patton |
—
|
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: Paula Patton | Statement: [Swing Vote, starring, Paula Patton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paula Patton Context triple: [Swing Vote, starring, Paula Patton]
-
A.
Paula Patton
chosen
Paula Patton is an American actress known for her roles in films such as "Precious," "Mission: Impossible – Ghost Protocol," and various romantic comedies and dramas.
-
B.
Emily Browning
Emily Browning is an Australian actress known for her roles in films such as "A Series of Unfortunate Events," "Sucker Punch," and "Sleeping Beauty."
-
C.
Erika Christensen
Erika Christensen is an American actress known for her roles in films like "Traffic" and "Flightplan" and the television series "Parenthood."
-
D.
Jessica Biel
Jessica Biel is an American actress and producer known for her roles in the TV series "7th Heaven" and films such as "The Texas Chainsaw Massacre" and "The Illusionist."
-
E.
Julie Hayden
Julie Hayden was an American short story writer and journalist known for her acclaimed collection "The Lists of the Past" and her work at The New Yorker.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c67c9d1c81908031eb77c124f119 |
completed | April 21, 2026, 12:36 a.m. |
Created at: April 16, 2026, 12:46 p.m.