Triple
T8990159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minbar of the Prophet |
E214767
|
entity |
| Predicate | hasLanguageOfReligiousUse |
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: [Minbar of the Prophet, hasLanguageOfReligiousUse, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfReligiousUse Context triple: [Minbar of the Prophet, hasLanguageOfReligiousUse, Arabic]
-
A.
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.
-
B.
usedForReligiousTexts
Indicates that something is used in the creation, preservation, or practice of religious texts or scriptures.
-
C.
isUsedByReligion
Indicates that something (such as an object, practice, text, or symbol) is employed or utilized within the context of a particular religion.
-
D.
languageOfWorship
chosen
Indicates the language in which religious worship, rituals, or liturgical practices are conducted.
-
E.
hasClericalLanguage
Indicates that something is expressed using formal, religious, or church-related language or terminology.
- 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_69ca839f76bc8190a4b7123cdd682199 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc68733548819096a5ba0ff41e43da |
completed | April 1, 2026, 12:36 a.m. |
| PD | Predicate disambiguation | batch_69cc5edba0f88190b97401636a076d7a |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:04 p.m.