Triple
T19466150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cherelle L. Parker |
E487004
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Cherelle L. Parker |
—
|
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: Cherelle L. Parker | Statement: [Cherelle L. Parker, name, Cherelle L. Parker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cherelle L. Parker Context triple: [Cherelle L. Parker, name, Cherelle L. Parker]
-
A.
Cherelle L. Parker
chosen
Cherelle L. Parker is an American politician who serves as the mayor of Philadelphia and is the first woman elected to the position in the city's history.
-
B.
Pam Veasey
Pam Veasey is an American television writer and producer best known for her work on crime and procedural dramas, including multiple series in the CSI franchise.
-
C.
Charlene McGee
Charlene McGee is the young girl with powerful and dangerous pyrokinetic abilities at the center of Stephen King’s novel "Firestarter."
-
D.
Kimberly J. Brown
Kimberly J. Brown is an American actress best known for playing Marnie Piper in Disney Channel’s Halloweentown film series.
-
E.
Tracey E. Edmonds
Tracey E. Edmonds is an American television and film producer and businesswoman known for her work in entertainment and media entrepreneurship.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633e1dccc819096feb1a514b9eb86 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:39 p.m.