Triple
T21649549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Confrontation with Elijah on Mount Carmel |
E534299
|
entity |
| Predicate | hasOpposingFigures |
P53524
|
FINISHED |
| Object | prophets of Baal |
—
|
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: prophets of Baal | Statement: [Confrontation with Elijah on Mount Carmel, hasOpposingFigures, prophets of Baal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpposingFigures Context triple: [Confrontation with Elijah on Mount Carmel, hasOpposingFigures, prophets of Baal]
-
A.
hasOpposingSide
Indicates that one entity possesses or is associated with another entity that lies on the opposite or facing side relative to a reference orientation or boundary.
-
B.
hasOpposingFront
Indicates that one entity’s front side is directly facing or oriented opposite to the front side of another entity.
-
C.
hasOpposingForceType
Indicates that one force is characterized as being of a type that opposes or counteracts another force.
-
D.
hasOpposingAgent
Indicates that an entity is opposed or counteracted by another agent in a given context or interaction.
-
E.
hasOpposingFaction
chosen
Indicates that one faction stands in opposition or conflict to another faction.
- 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef59131c88819082df8e5b87f5954b |
completed | April 27, 2026, 12:39 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:35 p.m.