Triple
T5021172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sultan Qaboos Grand Mosque |
E112850
|
entity |
| Predicate | openToNonMuslims |
P61576
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sultan Qaboos Grand Mosque, openToNonMuslims, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openToNonMuslims Context triple: [Sultan Qaboos Grand Mosque, openToNonMuslims, true]
-
A.
isNonSectarian
Indicates that an organization, institution, or activity is not affiliated with, restricted to, or biased toward any particular religious sect or denomination.
-
B.
isNonReligious
Indicates that an entity does not adhere to, practice, or identify with any religion or religious belief system.
-
C.
religiousReception
Indicates a relationship where one entity formally receives, welcomes, or hosts another in a specifically religious or faith-based context.
-
D.
religiousAttitude
Indicates an entity’s stance, disposition, or orientation toward religion or religious beliefs.
-
E.
relationToIslam
Indicates how an entity is connected or related to Islam, such as through belief, practice, affiliation, or influence.
- F. None of above. chosen
Provenance (4 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd736399ac8190aa38efc4b4edc6a2 |
completed | March 20, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69bd714ecfe08190b5830cfc1c74fa17 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd72e1b7cc8190b2e621fdf8f22e38 |
completed | March 20, 2026, 4:16 p.m. |
Created at: March 20, 2026, 1:36 p.m.