Triple
T15350941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | سورة تبت |
E367048
|
entity |
| Predicate | سبب النزول |
P118219
|
FINISHED |
| Object | تكذيب أبي لهب للنبي محمد صلى الله عليه وسلم |
—
|
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: تكذيب أبي لهب للنبي محمد صلى الله عليه وسلم | Statement: [سورة تبت, سبب النزول, تكذيب أبي لهب للنبي محمد صلى الله عليه وسلم]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: سبب النزول Context triple: [سورة تبت, سبب النزول, تكذيب أبي لهب للنبي محمد صلى الله عليه وسلم]
-
A.
سبب التسمية
Indicates the reason or cause behind assigning a particular name to something.
-
B.
التأثير
Indicates a relationship where one entity produces a change or has an influence on another entity or its state.
-
C.
causeOfDownfall
Indicates a factor, event, or agent that brings about the failure, ruin, or collapse of someone or something.
-
D.
סיבת זכייה
Indicates the reason or cause for which an entity wins or is awarded something.
-
E.
السمعة
Indicates the reputation or public perception associated with an entity based on others’ opinions or past actions.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e290efc8190b22c95dcd3e5f57f |
completed | April 16, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69deca991e5081908b0df3d1ee7d5338 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2e413481909d9180a8d78d2c17 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:17 a.m.