Triple
T24899248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | لوط |
E623528
|
entity |
| Predicate | يعد_في_الإسلام |
P26930
|
FINISHED |
| Object | من_الأنبياء_الصالحين |
—
|
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: من_الأنبياء_الصالحين | Statement: [لوط, يعد_في_الإسلام, من_الأنبياء_الصالحين]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: يعد_في_الإسلام Context triple: [لوط, يعد_في_الإسلام, من_الأنبياء_الصالحين]
-
A.
positionInIslam
chosen
Indicates the specific religious role, rank, or status an entity holds within the context of Islam.
-
B.
representsIslamicIdentity
Indicates that an entity embodies, expresses, or is associated with Islamic religious, cultural, or communal identity.
-
C.
positionOnIslam
Indicates the stance, viewpoint, or attitude that an entity holds toward Islam.
-
D.
تاريخ اعتناق الإسلام
Indicates the point in time at which an entity adopted or converted to Islam.
-
E.
knownInIslamAs
Indicates that an entity is referred to by a particular name, title, or designation specifically within the context of Islam or Islamic tradition.
- 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_69e2fac797cc8190b30d77f4121099ac |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f43043512481909501a3979cac9947 |
completed | May 1, 2026, 4:46 a.m. |
| PD | Predicate disambiguation | batch_69f420fd375c81908ea4a4e60b76ee8f |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 5:26 a.m.