Triple
T7849197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spin City |
E182000
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Connie Britton |
E248789
|
NE FINISHED |
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: Connie Britton | Statement: [Spin City, starring, Connie Britton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Connie Britton Context triple: [Spin City, starring, Connie Britton]
-
A.
Connie Britton
chosen
Connie Britton is an American actress best known for her roles in television series such as "Friday Night Lights," "Nashville," and "The White Lotus."
-
B.
Angie Harmon
Angie Harmon is an American actress and former model best known for her starring role as detective Jane Rizzoli on the television series "Rizzoli & Isles."
-
C.
Elizabeth Gilliland
Elizabeth Gilliland was a woman after whom the town of Elizabethtown in New York was named, likely an early settler or figure of local historical significance.
-
D.
Melissa Cobb
Melissa Cobb is an American film producer best known for her work on major animated features, including the Kung Fu Panda franchise.
-
E.
Lynn Collins
Lynn Collins is an American actress known for her roles in films such as X-Men Origins: Wolverine and John Carter, as well as various television series.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18e989ac819090e459b77d8932d3 |
completed | March 31, 2026, 12:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5b0515c08190b866a39749d54849 |
completed | March 31, 2026, 5:26 a.m. |
Created at: March 30, 2026, 4:50 p.m.