Triple
T11984578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Bucket |
E285244
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Grandpa Joe |
E285245
|
NE FINISHED |
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: Grandpa Joe | Statement: [Charlie Bucket, relative, Grandpa Joe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grandpa Joe Context triple: [Charlie Bucket, relative, Grandpa Joe]
-
A.
Grandpa Joe
chosen
Grandpa Joe is Charlie Bucket’s elderly, spirited grandfather who joins him on the fantastical tour of Willy Wonka’s chocolate factory in the 2005 film adaptation.
-
B.
Uncle Joe
Uncle Joe was the nickname of Joseph Gurney Cannon, a powerful early 20th-century Speaker of the U.S. House of Representatives known for his strong control over congressional proceedings.
-
C.
Uncle Joe
Uncle Joe is a colloquial nickname for Joseph Stalin, the Soviet dictator who led the USSR through World War II and oversaw widespread political repression.
-
D.
Grandpa George
Grandpa George is one of Charlie Bucket’s elderly, bedridden grandparents in Roald Dahl’s novel "Charlie and the Chocolate Factory."
-
E.
Uncle Bob
Uncle Bob is the nickname of Robert C. Martin, a prominent software engineer and author known for his influential work on clean code practices and agile software development.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903973c848190aac871d6dfecc74b |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a5b024c81909e4ccfd7dec7edb3 |
completed | May 2, 2026, 2:29 p.m. |
Created at: April 8, 2026, 9:46 p.m.