Triple
T21148095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beelzebub |
E521113
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Baal Zebub |
—
|
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: Baal Zebub | Statement: [Beelzebub, alsoKnownAs, Baal Zebub]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baal Zebub Context triple: [Beelzebub, alsoKnownAs, Baal Zebub]
-
A.
Beelzebub
chosen
Beelzebub is a prominent demon figure in Christian and literary tradition, often depicted as a high-ranking fallen angel and close associate of Satan.
-
B.
Baal
Baal is a prominent ancient Near Eastern storm and fertility god widely worshipped across Phoenician and Canaanite cultures.
-
C.
Baal
Baal is a powerful Prime Evil demon and one of the main antagonists in the Diablo video game series, known especially as the Lord of Destruction.
-
D.
Baal
Baal is a 1918 expressionist play by Bertolt Brecht that follows the amoral, self-destructive life of a bohemian poet.
-
E.
Azazel
Azazel is a powerful yellow-eyed demon from the television series "Supernatural," known for orchestrating the events that shape Sam and Dean Winchester’s destinies.
- 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_69e0b50c6a848190a4e525a77a319b8a |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e723fe9da88190b65c370b1efcbb96 |
completed | April 21, 2026, 7:15 a.m. |
Created at: April 16, 2026, 2:58 p.m.