Triple
T3285899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hell |
E68979
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | 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: Inferno | Statement: [Hell, hasAlternativeName, Inferno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inferno Context triple: [Hell, hasAlternativeName, Inferno]
-
A.
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.
-
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 a 1980s action thriller film best known for its desert survival and revenge storyline, directed by John G. Avildsen.
-
D.
The Inferno
The Inferno is the passionate and raucous student section that supports the Arizona State Sun Devils football team at their home games.
-
E.
Inferno (film)
Inferno is a 2016 mystery thriller film based on Dan Brown’s novel, following symbologist Robert Langdon as he races to stop a global catastrophe linked to Dante’s "Divine Comedy."
- 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_69ad859c463481909ca4be267336c290 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb03918c48190987d7cfd3bda9716 |
completed | March 8, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3cd5f508190ac5abc2dcdf0957d |
completed | March 12, 2026, 5:11 p.m. |
Created at: March 8, 2026, 3:10 p.m.