Triple
T17018470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of Grace |
E412881
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Faye Grant |
—
|
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: Faye Grant | Statement: [State of Grace, portrayedBy, Faye Grant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faye Grant Context triple: [State of Grace, portrayedBy, Faye Grant]
-
A.
Faye Grant
chosen
Faye Grant is an American actress best known for her role as Dr. Juliet Parrish in the 1980s science fiction television miniseries "V."
-
B.
Faye Medwick
Faye Medwick is a fictional character appearing in the work titled "Chapter Two."
-
C.
Faye Ward
Faye Ward is a British film and television producer known for her work on acclaimed projects such as the historical drama "Suffragette."
-
D.
Faye Brookes
Faye Brookes is an English actress best known for her role as Kate Connor in the long-running ITV soap opera Coronation Street.
-
E.
Jaye Griffiths
Jaye Griffiths is a British actress known for her work in television dramas and science fiction series, including roles in shows like "Doctor Who," "Casualty," and "Silent Witness."
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d481a0988190a13d0928e0c7ebbf |
completed | April 18, 2026, 6:59 p.m. |
Created at: April 10, 2026, 5:33 a.m.