Triple
T4757726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inferno |
E105627
|
entity |
| Predicate | circleFiveTheme |
P25955
|
FINISHED |
| Object | wrath and sullenness |
—
|
LITERAL 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: wrath and sullenness | Statement: [Inferno, circleFiveTheme, wrath and sullenness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: circleFiveTheme Context triple: [Inferno, circleFiveTheme, wrath and sullenness]
-
A.
circleType
Indicates the specific classification or category of a circle within a given context or system.
-
B.
cycleType
Indicates the specific kind or category of cycle involved in a repeated or cyclical process or relationship.
-
C.
circles
Indicates that one entity moves around another entity along a roughly circular path or orbit.
-
D.
themeFor
chosen
Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
-
E.
themeExamples
Indicates that the related entity serves as an example or illustration of the theme expressed by the subject.
- F. None of above.
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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650ad0f88190844bfcb46b3071c2 |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd6225c9488190afee5bb3619d0365 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:20 p.m.