Triple
T24307884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | al-Masih |
E612582
|
entity |
| Predicate | hasOppositeFigure |
P83315
|
FINISHED |
| Object | al-Masih al-Dajjal (the false messiah) |
—
|
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: al-Masih al-Dajjal (the false messiah) | Statement: [al-Masih, hasOppositeFigure, al-Masih al-Dajjal (the false messiah)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOppositeFigure Context triple: [al-Masih, hasOppositeFigure, al-Masih al-Dajjal (the false messiah)]
-
A.
hasOppositeComponent
Indicates that one component is related to another as its opposite or contrasting counterpart within a system or structure.
-
B.
hasOppositeStructure
Indicates that one entity possesses a structure that is the inverse or opposite in form, arrangement, or organization relative to another entity.
-
C.
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.
-
D.
hasOppositeDirectionTo
Indicates that one entity’s direction is exactly reversed or opposed to the direction of another entity.
-
E.
hasOpposingAgent
chosen
Indicates that an entity is opposed or counteracted by another agent in a given context or interaction.
- 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_69e2d7d91bb48190bc5377d17a85fb21 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2922821248190a1b274f839251ddc |
completed | April 29, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69f1c45c6ec081908401b69424428100 |
completed | April 29, 2026, 8:42 a.m. |
Created at: April 18, 2026, 1:31 a.m.