Triple
T26309441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | عام الحزن |
E661778
|
entity |
| Predicate | مرتبط_ب_موضوع |
P107052
|
FINISHED |
| Object | تاريخ الدعوة الإسلامية في مكة |
—
|
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: تاريخ الدعوة الإسلامية في مكة | Statement: [عام الحزن, مرتبط_ب_موضوع, تاريخ الدعوة الإسلامية في مكة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: مرتبط_ب_موضوع Context triple: [عام الحزن, مرتبط_ب_موضوع, تاريخ الدعوة الإسلامية في مكة]
-
A.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
B.
relatedPass
Indicates that one pass is associated with or connected to another pass in some relevant way.
-
C.
повʼязанеЗ
Indicates a general association or connection between one entity and another.
-
D.
associatedWithSubject
chosen
Indicates a general relationship or connection between an entity and a subject, without specifying the exact nature of that association.
-
E.
relatedToTerm
Indicates a general, non-specific relationship or association between one term and 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_69ee812dacfc81908484aade9120fba9 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620debeb48190b7db395fb86cf8d9 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 26, 2026, 10:21 p.m.