Triple
T21943496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelli Garner |
E541878
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Kelli |
—
|
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: Kelli | Statement: [Kelli Garner, givenName, Kelli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kelli Context triple: [Kelli Garner, givenName, Kelli]
-
A.
Kelli
chosen
Kelli is a feminine given name, typically considered a variant spelling of Kelly.
-
B.
Kayely
Kayely is an alternate name for the Kayeli language, an Austronesian language historically spoken on Buru Island in Indonesia.
-
C.
Kayla
Kayla is a central character in the tech-comedy web series "Hacks," known for her over-the-top personality and chaotic presence in the workplace.
-
D.
Kayla
Kayla is a young child in Jesmyn Ward’s novel "Sing, Unburied, Sing," symbolizing innocence and hope amid her family’s struggles with racism, addiction, and generational trauma in rural Mississippi.
-
E.
Kelsey
Kelsey is a given name most famously associated with American actor and comedian Kelsey Grammer.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242515ec8190b015bf8c7b13be85 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:56 p.m.