Triple
T36049804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doukhobors |
E1042774
|
entity |
| Predicate | viewOnWeapons |
P104433
|
FINISHED |
| Object | rejection of bearing arms |
—
|
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: rejection of bearing arms | Statement: [Doukhobors, viewOnWeapons, rejection of bearing arms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewOnWeapons Context triple: [Doukhobors, viewOnWeapons, rejection of bearing arms]
-
A.
positionOnWeapons
chosen
Indicates a stance, policy, or viewpoint that an entity holds regarding weapons or weapon-related issues.
-
B.
weaponOfInterest
Indicates that an entity is a weapon that is specifically relevant, notable, or targeted for attention within a given context or scenario.
-
C.
weaponsBay
Indicates that one entity serves as the weapons bay (storage or housing area for weapons) of another entity.
-
D.
weaponsUsed
Indicates that one entity employed or utilized another entity as a weapon in carrying out an action or event.
-
E.
weaponExamples
Indicates that one entity is an example or instance of a weapon associated with another entity.
- 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_69f76e2e41f8819091f9fb0536920fec |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
Created at: May 3, 2026, 4:07 p.m.