Triple
T20878521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fizzy Lifting Drinks |
E514083
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Roald Dahl |
—
|
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: Roald Dahl | Statement: [Fizzy Lifting Drinks, creator, Roald Dahl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roald Dahl Context triple: [Fizzy Lifting Drinks, creator, Roald Dahl]
-
A.
Roald Dahl
chosen
Roald Dahl was a British author famed for his darkly imaginative children's books such as "Charlie and the Chocolate Factory" and "Matilda," as well as his work in adult fiction and screenwriting.
-
B.
Dahl
Dahl is a locality in Germany situated along the Volme River, known for its scenic valley setting and historical connection to the surrounding Ruhr region.
-
C.
Dahl
Dahl is a common Norwegian surname borne by numerous notable figures in fields such as computer science, literature, and the arts.
-
D.
Michael Bond
Michael Bond was a British author best known for creating the beloved children's character Paddington Bear.
-
E.
Dodie Smith
Dodie Smith was an English novelist and playwright best known for writing the children's classic "The Hundred and One Dalmatians."
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c6775f108190a79cd5e8c31cecf6 |
completed | April 21, 2026, 12:36 a.m. |
Created at: April 16, 2026, 12:45 p.m.