Triple
T18498848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Divine Comedy |
E452015
|
entity |
| Predicate | protagonist |
P268
|
FINISHED |
| Object | Dante |
—
|
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: Dante | Statement: [Divine Comedy, protagonist, Dante]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dante Context triple: [Divine Comedy, protagonist, Dante]
-
A.
Dante
Dante Fascell was a long-serving American Democratic politician from Florida who represented the Miami area in the U.S. House of Representatives and played a key role in foreign affairs legislation.
-
B.
Dante
Dante is an acclaimed Italian production designer and art director renowned for his work on numerous major films, including collaborations with directors like Federico Fellini and Martin Scorsese.
-
C.
Dante
chosen
Dante is a given name of Italian origin most famously associated with the medieval poet Dante Alighieri, author of "The Divine Comedy."
-
D.
Dante
Dante is the loyal, goofy Xoloitzcuintli dog who accompanies Miguel on his journey through the Land of the Dead in Pixar’s animated film "Coco."
-
E.
Dante
Dante is a character from the television series "The Wire," known as Omar Little’s boyfriend and a member of his stickup crew in Baltimore’s criminal underworld.
- 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e532c275388190aafe891d0202f82e |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 11:36 a.m.