Triple
T26309437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | عام الحزن |
E661778
|
entity |
| Predicate | مرتبط_ب_شخصية_محورية |
P93589
|
FINISHED |
| Object | خديجة بنت خويلد |
—
|
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: خديجة بنت خويلد | Statement: [عام الحزن, مرتبط_ب_شخصية_محورية, خديجة بنت خويلد]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: مرتبط_ب_شخصية_محورية Context triple: [عام الحزن, مرتبط_ب_شخصية_محورية, خديجة بنت خويلد]
-
A.
relatedCharacter
Indicates that one character has a specified relationship or association with another character.
-
B.
associatedWithCharacterRole
Indicates that one entity has a connection or linkage to a specific character role played or held by another entity.
-
C.
hasProtagonistRelationship
Indicates that there exists a central, story-driving relationship involving the protagonist and another entity within a narrative.
-
D.
isPivotalForCharacter
chosen
Indicates that something plays a crucial, defining role in shaping a character’s development, decisions, or narrative arc.
-
E.
relatedCharacterContext
Indicates a contextual relationship between characters, such as roles, interactions, or situational connections that link them within a specific narrative or setting.
- 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_69f60ee64ce08190b9fbede178cc6f28 |
completed | May 2, 2026, 2:49 p.m. |
| PD | Predicate disambiguation | batch_69f602d2ec748190ae95154f34c7878f |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 10:21 p.m.