Triple
T21891859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maggie Renzi |
E540569
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Sunshine State |
—
|
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: Sunshine State | Statement: [Maggie Renzi, notableWork, Sunshine State]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sunshine State Context triple: [Maggie Renzi, notableWork, Sunshine State]
-
A.
Sunshine State
The Sunshine State is the popular nickname for the U.S. state of Florida, known for its warm climate, beaches, and tourism.
-
B.
Sunshine State
chosen
Sunshine State is a 2002 independent drama film by John Sayles that explores race, development, and community tensions in a changing Florida coastal town.
-
C.
Sunflower State
The Sunflower State is the popular nickname for Kansas, a U.S. state known for its vast plains and fields of sunflowers.
-
D.
Peach State
Peach State is a popular nickname for the U.S. state of Georgia, referencing its reputation for producing high-quality peaches.
-
E.
SUNSTATE
SUNSTATE is the radio callsign used by Sunstate Airlines, a regional carrier operating under the QantasLink brand in Australia.
- 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_69e0c47a95908190ae3e19b716accb3d |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fc3727c8190b4d5d5a44aa2e55e |
completed | April 28, 2026, 8:59 p.m. |
Created at: April 16, 2026, 7:06 p.m.