Triple
T17844292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyla Pratt |
E445615
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Pratt |
—
|
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: Pratt | Statement: [Kyla Pratt, familyName, Pratt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pratt Context triple: [Kyla Pratt, familyName, Pratt]
-
A.
Pratt
chosen
Pratt is a common English surname borne by various notable individuals across fields such as entertainment, politics, and academia.
-
B.
Widener
Widener is an American surname most prominently associated with a wealthy Philadelphia family known for their influence in business, philanthropy, and the arts.
-
C.
Doane
Doane is a surname most notably associated with William Croswell Doane, the first Episcopal Bishop of Albany and a prominent 19th-century American church leader.
-
D.
Princeton
Princeton is a historic New Jersey town best known as the site of the pivotal 1777 Battle of Princeton during the American Revolutionary War and as home to Princeton University.
-
E.
Princeton
Princeton is a small city in southwestern Indiana known as the county seat of Gibson County and a regional hub for manufacturing and agriculture.
- 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_69d8b9f1a6d881909f024bc603111cdb |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48ff980048190b496c55b83b3b318 |
completed | April 19, 2026, 8:19 a.m. |
Created at: April 10, 2026, 10:16 a.m.