Triple
T21036037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Percy Weasley |
E518191
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Percy |
—
|
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: Percy | Statement: [Percy Weasley, givenName, Percy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Percy Context triple: [Percy Weasley, givenName, Percy]
-
A.
Percy
Percy is a character connected to the Paradise Falls diner, likely serving as one of its notable staff or regular patrons within its narrative setting.
-
B.
Percy
chosen
Percy is a masculine given name of Old French origin, famously borne by American physicist and Nobel laureate Percy W. Bridgman.
-
C.
Percy
Percy is the historic English noble family that produced numerous prominent aristocrats, soldiers, and politicians, notably the Dukes of Northumberland.
-
D.
Percy
Percy is a sadistic and cowardly prison guard from Stephen King’s novel "The Green Mile" and its film adaptation.
-
E.
Percy LeSueur
Percy LeSueur was a prominent early 20th-century Canadian ice hockey goaltender and later coach and manager, recognized as a Hall of Famer for his contributions to the sport.
- 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_69e0b503275c8190afd9a163f997c709 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc865ca88190abf336ee9012fa77 |
completed | April 21, 2026, 4:26 a.m. |
Created at: April 16, 2026, 2:02 p.m.