Triple
T9801680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McKaley Miller |
E237851
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | McKaley Miller |
E237851
|
NE FINISHED |
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: McKaley Miller | Statement: [McKaley Miller, name, McKaley Miller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: McKaley Miller Context triple: [McKaley Miller, name, McKaley Miller]
-
A.
McKaley Miller
chosen
McKaley Miller is an American actress best known for her role as Rose Hattenbarger on the television series "Hart of Dixie."
-
B.
Kelsey Burrell
Kelsey Burrell is known as the child of the Jamaican-American reggae fusion singer and rapper Shaggy.
-
C.
Kellie Miller
Kellie Miller is one of the plaintiffs who challenged Tennessee’s ban on recognizing same-sex marriages in the federal court case Tanco v. Haslam.
-
D.
Kelsey Gonzalez
Kelsey Gonzalez is a visual artist and designer known for creating cover art, including work for the band Bush.
-
E.
Brooke Mueller
Brooke Mueller is an American actress and real estate investor best known for her high-profile marriage to actor Charlie Sheen and appearances on reality television.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca84dd4608819097ff4ed00feca280 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda62b41048190bcef70a7591830c6 |
completed | April 1, 2026, 11:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1c44edac48190a44fdfb858d0dbba |
completed | April 5, 2026, 2:09 a.m. |
Created at: March 30, 2026, 8:29 p.m.