Triple
T38314632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abdelrahman |
E1033788
|
entity |
| Predicate | religiousLinguisticCategory |
P202144
|
FINISHED |
| Object | Abd-name (servant-of-God name) |
—
|
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: Abd-name (servant-of-God name) | Statement: [Abdelrahman, religiousLinguisticCategory, Abd-name (servant-of-God name)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousLinguisticCategory Context triple: [Abdelrahman, religiousLinguisticCategory, Abd-name (servant-of-God name)]
-
A.
languageOfReligion
Indicates the language in which a particular religion is traditionally expressed, practiced, or documented.
-
B.
languageOfReligiousLife
Indicates the language primarily used in the religious practices, rituals, or spiritual life associated with an entity.
-
C.
religiousTextCategory
Indicates that a religious text belongs to or is classified under a particular category or type.
-
D.
languageOfScripturalTradition
Indicates the language in which a given scriptural or religious textual tradition is expressed or transmitted.
-
E.
religiousSpectrum
Indicates a relationship that places entities along a range or continuum of religious belief, practice, or affiliation.
- 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_69f76e132c408190969b3d35c04b87ae |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a0058c341ac8190825067dc25158839 |
completed | May 10, 2026, 10:06 a.m. |
| PD | Predicate disambiguation | batch_6a005857249c81908b27587b84d84dbb |
completed | May 10, 2026, 10:05 a.m. |
| PDg | Predicate description generation | batch_6a0058c26638819085d8cbaa0bd4ccf0 |
completed | May 10, 2026, 10:06 a.m. |
Created at: May 3, 2026, 4:30 p.m.