Triple
T37847661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inferno, Canto V |
E943948
|
entity |
| Predicate | primarySinCategory |
P100054
|
FINISHED |
| Object | incontinence |
—
|
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: incontinence | Statement: [Inferno, Canto V, primarySinCategory, incontinence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySinCategory Context triple: [Inferno, Canto V, primarySinCategory, incontinence]
-
A.
primarySin
chosen
Indicates a fundamental or chief moral wrongdoing attributed to an entity, often viewed as the root or most significant sin in a given context.
-
B.
primaryCauseCategory
Indicates the main type or classification of cause responsible for an outcome or event.
-
C.
primaryType
Indicates the main or most fundamental category or classification assigned to an entity, distinguishing it from any secondary or auxiliary types.
-
D.
primaryEventType
Indicates the main or most significant category of event with which an entity, record, or occurrence is primarily associated.
-
E.
primaryCatch
Indicates that an entity is the main or most significant target, recipient, or object captured or obtained in a given context.
- 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_69f76eed4d9c81908b1b71ba9e3b61fe |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:19 p.m.