Triple
T1055191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hazaras |
E22784
|
entity |
| Predicate | religiousLanguage |
P2154
|
FINISHED |
| Object | Arabic (for liturgy) |
—
|
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: Arabic (for liturgy) | Statement: [Hazaras, religiousLanguage, Arabic (for liturgy)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousLanguage Context triple: [Hazaras, religiousLanguage, Arabic (for liturgy)]
-
A.
religiousElement
chosen
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
B.
positionOnReligiousLanguage
Indicates a stance or viewpoint someone holds regarding how religious language should be understood, interpreted, or used.
-
C.
ethnicReligion
Indicates that a religion is closely associated with a particular ethnic group, often tied to that group’s culture, ancestry, or identity.
-
D.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
-
E.
religiousCulturalContext
Indicates the religious or cultural setting, tradition, or framework within which an entity, practice, or event occurs or is interpreted.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8d79268819080f3f3f497e91c58 |
completed | March 1, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69a4b731e25c8190b5ea8466648c2c9a |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.