Triple
T19836378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gospel of Nicodemus |
E476605
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Satan |
—
|
NE NERFINISHED |
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: Satan | Statement: [Gospel of Nicodemus, featuresCharacter, Satan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Satan Context triple: [Gospel of Nicodemus, featuresCharacter, Satan]
-
A.
Satan
Satan is a central demonic figure and primary antagonist in the manga and anime series Blue Exorcist, portrayed as the powerful king of demons and the source of the protagonist’s conflict.
-
B.
Satan
chosen
Satan is a central figure in Abrahamic religions, typically depicted as the embodiment of evil and the adversary of God and humankind.
-
C.
Satan
Satan is a track by the electronic music duo Orbital, known for its dark, driving sound and prominent use in their live performances.
-
D.
Satana
Satana is a Marvel Comics supernatural antiheroine and sorceress, the half-demon daughter of Satan and sister of Daimon Hellstrom.
-
E.
Satana
Satana is a town in the Nashik district of Maharashtra, India, known for its agricultural markets and proximity to several religious and historical sites.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656d275608190841b23de167c401e |
completed | April 20, 2026, 4:39 p.m. |
Created at: April 10, 2026, 1:50 p.m.