Triple
T4524712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shabana Rehman |
E103348
|
entity |
| Predicate | religionCriticized |
P46422
|
FINISHED |
| Object | Islamic extremism |
—
|
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: Islamic extremism | Statement: [Shabana Rehman, religionCriticized, Islamic extremism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religionCriticized Context triple: [Shabana Rehman, religionCriticized, Islamic extremism]
-
A.
religiousCritic
chosen
Indicates that one entity criticizes, challenges, or expresses disapproval of another entity on religious grounds or regarding religious beliefs, practices, or institutions.
-
B.
subjectReligion
Indicates that the subject is associated with, practices, or adheres to a particular religion.
-
C.
religiousControversy
Indicates a relationship in which entities are involved in a dispute, conflict, or debate specifically concerning religious beliefs, practices, or institutions.
-
D.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
E.
bearerReligion
Indicates that a bearer (such as a person or entity) adheres to, practices, or is associated with a particular religion.
- 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_69bd43dba59881908cf59b31df8c7ae1 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5773341c8190bf27745feb863575 |
completed | March 20, 2026, 2:19 p.m. |
| PD | Predicate disambiguation | batch_69bd521cf77c819083852de3094d1377 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:03 p.m.