Triple
T20278147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commedia dell’arte |
E503067
|
entity |
| Predicate | hasStockCharacter |
P139519
|
FINISHED |
| Object | Pantalone |
—
|
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: Pantalone | Statement: [Commedia dell’arte, hasStockCharacter, Pantalone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pantalone Context triple: [Commedia dell’arte, hasStockCharacter, Pantalone]
-
A.
Pantalone
chosen
Pantalone is a classic commedia dell'arte character, typically portrayed as a wealthy, miserly old Venetian merchant and frequent foil to the clever servant Harlequin.
-
B.
Jupe
Jupe is a surname most notably associated with English actor Noah Jupe.
-
C.
Pant
Pant is an Indian surname traditionally associated with Brahmin communities, particularly in the Himalayan regions of Uttarakhand and Nepal.
-
D.
Trottiera
Trottiera is one of the traditional bells housed in St Mark's Campanile in Venice, historically used to signal specific civic or religious events.
-
E.
Pantaloon in Black
"Pantaloon in Black" is a short story by William Faulkner that forms part of his collection *Go Down, Moses*, exploring themes of grief, racial tension, and injustice in the American South.
- 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e675e59f7c819086638b871ecbbd40 |
completed | April 20, 2026, 6:52 p.m. |
Created at: April 16, 2026, 10:35 a.m.