Triple
T18055414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grayson Perry |
E432025
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Grayson |
—
|
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: Grayson | Statement: [Grayson Perry, givenName, Grayson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grayson Context triple: [Grayson Perry, givenName, Grayson]
-
A.
Grayson
Grayson is an unincorporated community located in Stanislaus County, California.
-
B.
Grayson
chosen
Grayson is the given name of British artist and Turner Prize winner Grayson Perry, known for his ceramic works and exploration of identity and gender.
-
C.
Grayson
Grayson is a surname of English origin borne by various notable individuals across politics, sports, and the arts.
-
D.
Grayson
Grayson is a heroic but somewhat dim-witted gray squirrel from the animated film "The Nut Job."
-
E.
Grayson Kent
Grayson Kent is a central character in the legal dramedy "Drop Dead Diva," portrayed as a charming and principled attorney who serves as the main love interest of the show's protagonist.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4c101dfb081908dc66f4b4967d8c7 |
completed | April 19, 2026, 11:48 a.m. |
Created at: April 10, 2026, 10:26 a.m.