Triple
T8643955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | سورة الصافات |
E204724
|
entity |
| Predicate | سبب تسميتها |
P7885
|
FINISHED |
| Object | افتتاحها بقسم الله بالصافات صفا من الملائكة |
—
|
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: افتتاحها بقسم الله بالصافات صفا من الملائكة | Statement: [سورة الصافات, سبب تسميتها, افتتاحها بقسم الله بالصافات صفا من الملائكة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: سبب تسميتها Context triple: [سورة الصافات, سبب تسميتها, افتتاحها بقسم الله بالصافات صفا من الملائكة]
-
A.
reasonForName
chosen
Indicates the explanation or cause behind why an entity has a particular name.
-
B.
reasonForEpithet
Indicates the cause, motivation, or circumstance that explains why a particular epithet is applied to an entity.
-
C.
reasonForTitle
Indicates the justification, cause, or basis for assigning a particular title to an entity.
-
D.
usesNameDueTo
Indicates that one entity adopts or applies a particular name for another entity specifically because of some motivating reason, circumstance, or dependency.
-
E.
nameGivesRiseTo
Indicates that one name, term, or designation leads to, causes, or results in the emergence or establishment of another.
- 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_69ca834ca1c88190a11ffb0200342fac |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4798852881909c03c5eadf805e49 |
completed | March 31, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69cc455d6d448190a2da2a319ac78c37 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:28 p.m.