Triple
T30636092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Michael and the Devil |
E779846
|
entity |
| Predicate | portraysRoleOfDevil |
P12222
|
FINISHED |
| Object | embodiment of evil |
—
|
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: embodiment of evil | Statement: [St Michael and the Devil, portraysRoleOfDevil, embodiment of evil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysRoleOfDevil Context triple: [St Michael and the Devil, portraysRoleOfDevil, embodiment of evil]
-
A.
viewOfDevil
chosen
Indicates a depiction, perspective, or representation in which the subject is shown or understood as the devil or in relation to the devil.
-
B.
stateOfDevils
Indicates a condition, status, or situation specifically associated with devils.
-
C.
roleInParadiseLost
Indicates the specific narrative or functional role an entity plays within the work *Paradise Lost*.
-
D.
portraysAdversary
Indicates that one entity depicts or represents another entity as an opponent, enemy, or rival.
-
E.
portraysUnderworld
Indicates that an entity depicts or represents the underworld or a subterranean realm in some medium or 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_69f224a50ebc81909b961a94c7f66b12 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd9ff026a48190bfec33deeb3b2c43 |
completed | May 8, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69fd97d805bc8190ba12f429d3ad04c7 |
completed | May 8, 2026, 7:59 a.m. |
Created at: April 29, 2026, 8:28 p.m.