Triple
T20525301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franco Fraticelli |
E503918
|
entity |
| Predicate | editedFilm |
P14416
|
FINISHED |
| Object | Inferno |
—
|
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: Inferno | Statement: [Franco Fraticelli, editedFilm, Inferno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inferno Context triple: [Franco Fraticelli, editedFilm, Inferno]
-
A.
Inferno
Inferno is the first cantica of Dante Alighieri’s Divine Comedy, depicting the poet’s allegorical journey through the nine circles of Hell.
-
B.
Inferno
Inferno is a distributed operating system developed at Bell Labs, known for its use of the Limbo programming language and its focus on portable, networked computing.
-
C.
Inferno
Inferno is an autobiographical novel by August Strindberg that chronicles his psychological crisis, occult obsessions, and descent into paranoia during his years in Paris.
-
D.
Inferno
"Inferno" is a 2016 mystery thriller film based on Dan Brown's novel, in which Irrfan Khan plays a key supporting role alongside Tom Hanks.
-
E.
Inferno
chosen
"Inferno" is a 1953 Technicolor 3D film noir thriller starring William Lundigan alongside Robert Ryan and Rhonda Fleming, noted for its desert survival plot and innovative use of 3D cinematography.
- 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_69e0b4b3a6e08190ae663701f50fab8e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a06504b48190b3f1defdc23a47d5 |
completed | April 20, 2026, 9:53 p.m. |
Created at: April 16, 2026, 11:37 a.m.