Triple
T8543374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 666 |
E202254
|
entity |
| Predicate | hasControversialContent |
P81772
|
FINISHED |
| Object | religious themes |
—
|
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: religious themes | Statement: [666, hasControversialContent, religious themes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasControversialContent Context triple: [666, hasControversialContent, religious themes]
-
A.
hasControversialAspect
chosen
Indicates that something includes an element, feature, or aspect that is disputed, debated, or likely to cause disagreement or public criticism.
-
B.
controversialBecause
Indicates that one entity is considered controversial specifically due to, or as a result of, its relationship with or association to another entity.
-
C.
controversialWork
Indicates that a work is the subject of significant public disagreement, debate, or dispute regarding its content, impact, or acceptability.
-
D.
controversyType
Indicates the specific kind or category of controversy associated with an entity or situation.
-
E.
roleInControversy
Indicates the specific part, involvement, or function an entity has within a particular controversy or disputed situation.
- 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_69ca832461e88190a654c5e44e233aa8 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6e381d4819084e230389a3ecb77 |
completed | March 31, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69cbd113e05c81908f4f3fc1b5925164 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:18 p.m.