Triple
T30890543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Girl Without Hands |
E786884
|
entity |
| Predicate | narrativeRoleOfDevil |
P101050
|
FINISHED |
| Object | tempter |
—
|
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: tempter | Statement: [The Girl Without Hands, narrativeRoleOfDevil, tempter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: narrativeRoleOfDevil Context triple: [The Girl Without Hands, narrativeRoleOfDevil, tempter]
-
A.
roleInParadiseLost
Indicates the specific narrative or functional role an entity plays within the work *Paradise Lost*.
-
B.
viewOfDevil
Indicates a depiction, perspective, or representation in which the subject is shown or understood as the devil or in relation to the devil.
-
C.
inNarrativeRole
chosen
Indicates that one entity participates in relation to another by occupying a specific narrative function or role within a story or discourse.
-
D.
moralNarrativeRole
Indicates the role an entity plays within a moral storyline or ethical framing, such as being portrayed as virtuous, villainous, victimized, or morally ambiguous.
-
E.
stateOfDevils
Indicates a condition, status, or situation specifically associated with devils.
- 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_69f224bbfa7c81908448e0c261c523e3 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
Created at: April 29, 2026, 8:49 p.m.