Triple
T17438880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brian Kelley |
E424095
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kelley |
—
|
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: Kelley | Statement: [Brian Kelley, familyName, Kelley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kelley Context triple: [Brian Kelley, familyName, Kelley]
-
A.
Kelley
chosen
Kelley is a surname most notably associated with Florence Kelley, a prominent American social and political reformer who fought for labor rights and child welfare in the late 19th and early 20th centuries.
-
B.
Keeley
Keeley is a feminine given name of English origin, often used both as a first name and surname.
-
C.
E-Kelly
E-Kelly is a prominent Nigerian music producer known for crafting hit songs across Afrobeats and contemporary African pop.
-
D.
Kelsey
Kelsey is a given name most famously associated with American actor and comedian Kelsey Grammer.
-
E.
Keally
Keally is a surname most notably associated with Francis Keally, an American architect active in the early to mid-20th century.
- 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44ff584cc81908207c163f19ff972 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 5:46 a.m.