Triple
T14210602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’Enfer |
E352216
|
entity |
| Predicate | hasEnglishTitle |
P3437
|
FINISHED |
| Object | The Inferno |
E105627
|
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: The Inferno | Statement: [L’Enfer, hasEnglishTitle, The Inferno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Inferno Context triple: [L’Enfer, hasEnglishTitle, The Inferno]
-
A.
The Inferno
The Inferno is the passionate and raucous student section that supports the Arizona State Sun Devils football team at their home games.
-
B.
Inferno
"Inferno" is a critically acclaimed short horror film by visual effects artist and director Mike Hill, known for its atmospheric storytelling and striking, cinematic imagery.
-
C.
Inferno
chosen
Inferno is the first cantica of Dante Alighieri’s Divine Comedy, depicting the poet’s allegorical journey through the nine circles of Hell.
-
D.
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.
-
E.
Inferno
Inferno is the third and final episode of the 1995 first-person shooter game The Ultimate Doom, featuring some of the most challenging levels set in a hellish environment.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de620dba0c8190bb77a1df10e1d3a7 |
completed | April 14, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd19574280819091bafd95a75983bf |
completed | May 7, 2026, 10:59 p.m. |
Created at: April 10, 2026, 1:05 a.m.