Triple
T23421607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sachi Parker |
E560670
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sachi 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: Sachi Parker | Statement: [Sachi Parker, name, Sachi Parker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sachi Parker Context triple: [Sachi Parker, name, Sachi Parker]
-
A.
Sachi Parker
chosen
Sachi Parker is an American actress and writer, known for her film and television roles as well as for being the daughter of Hollywood star Shirley MacLaine.
-
B.
Kimberly Parker
Kimberly Parker is a film producer known for her work on the 2013 drama "A Teacher."
-
C.
Andrea Parker
Andrea Parker is an American actress best known for her role as the enigmatic Miss Parker on the television series "The Pretender."
-
D.
Christie Parker
Christie Parker is a fictional character played by actress Jennifer Crystal Foley, best known from her work in American television.
-
E.
Nicole Parker
Nicole Parker is an American actress and comedian best known for her sketch work on MADtv and roles in parody films.
- 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_69e2454cb1108190ab21ada5411a7146 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a546c08c8190b57d90e88034eef3 |
completed | April 29, 2026, 6:29 a.m. |
Created at: April 17, 2026, 5:46 p.m.