Triple
T21664351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cassie Gaines |
E534670
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Steve Gaines |
—
|
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: Steve Gaines | Statement: [Cassie Gaines, relative, Steve Gaines]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Gaines Context triple: [Cassie Gaines, relative, Steve Gaines]
-
A.
Steve Gaines
chosen
Steve Gaines was an American guitarist, singer, and songwriter best known for his work with the Southern rock band Lynyrd Skynyrd in the mid-1970s.
-
B.
Steven Gaines
Steven Gaines is an American author and journalist known for his biographies and works on popular culture, fashion, and New York society.
-
C.
Steve Gainer
Steve Gainer is an American cinematographer known for his work on feature films, television series, and music videos.
-
D.
Ray Gaines
Ray Gaines is the heroic Los Angeles Fire Department rescue pilot portrayed by Dwayne Johnson in the disaster film "San Andreas."
-
E.
Greg Ganske
Greg Ganske is an American plastic surgeon and Republican politician who represented Iowa in the U.S. House of Representatives from 1995 to 2003.
- 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c0a2a58819086db5b5c1c0f3371 |
completed | April 27, 2026, 2 p.m. |
Created at: April 16, 2026, 6:36 p.m.