Triple
T1918838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yazidism |
E40078
|
entity |
| Predicate | mischaracterizedAs |
P4002
|
FINISHED |
| Object | devil worship by some outsiders |
—
|
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: devil worship by some outsiders | Statement: [Yazidism, mischaracterizedAs, devil worship by some outsiders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mischaracterizedAs Context triple: [Yazidism, mischaracterizedAs, devil worship by some outsiders]
-
A.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
B.
misappliedAs
chosen
Indicates that something has been used, interpreted, or assigned in an incorrect, inappropriate, or unintended way.
-
C.
disguisedAs
Indicates that one entity is intentionally presenting itself as, or made to appear as, another entity in order to conceal its true identity.
-
D.
legalCharacterization
Indicates how an action, event, or situation is classified or characterized under a specific legal framework or set of laws.
-
E.
misuseCanConstitute
Indicates that improper or incorrect use of something can amount to, or be considered as, a particular offense, violation, or condition.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb211eda88190865de7a0522a453d |
completed | March 7, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69abafed2ab481908920334e77b1021b |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.