Triple
T3238065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arba'a Rukun Mosque |
E67900
|
entity |
| Predicate | languageOfReligiousPractice |
P3115
|
FINISHED |
| Object | Arabic |
—
|
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 | Statement: [Arba'a Rukun Mosque, languageOfReligiousPractice, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfReligiousPractice Context triple: [Arba'a Rukun Mosque, languageOfReligiousPractice, Arabic]
-
A.
languageOfWorship
chosen
Indicates the language in which religious worship, rituals, or liturgical practices are conducted.
-
B.
usedForReligiousLanguage
Indicates that something is employed specifically in the context of religious language, such as for expressing, communicating, or performing religious beliefs, practices, or rituals.
-
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.
languageOfCeremony
Indicates the language in which a ceremony is conducted or officially performed.
-
E.
languageOfPrimaryCult
Indicates that a specified language is the main or dominant language used in a particular cult’s primary religious practices or rituals.
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaef3b04081908ce9b788e2e5c63c |
completed | March 8, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69ada4159e0481908cbbdd750f5e08c7 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:08 p.m.