Triple
T35967347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sīrat ʿAntar |
E1040180
|
entity |
| Predicate | featuresLoveStoryWith |
P118065
|
FINISHED |
| Object | ʿAbla bint Malik |
E1044804
|
NE 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: ʿAbla bint Malik | Statement: [Sīrat ʿAntar, featuresLoveStoryWith, ʿAbla bint Malik]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresLoveStoryWith Context triple: [Sīrat ʿAntar, featuresLoveStoryWith, ʿAbla bint Malik]
-
A.
featuresStar
Indicates that one entity prominently includes or showcases another entity as a main star or featured performer.
-
B.
romanticGenreElementIn
Indicates that something functions as a romantic-genre element within a larger work or context.
-
C.
romanticLeadIn
chosen
Indicates that one entity is the primary romantic interest or central romantic partner of another within a narrative or context.
-
D.
fellInLoveWith
Indicates that one entity developed romantic love or deep affectionate feelings toward another entity.
-
E.
featuresStorytellingLyrics
Indicates that the subject’s lyrics narrate a story or sequence of events rather than focusing solely on abstract or non-narrative content.
- F. None of above.
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_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38b70e46f08190a95a61bf009340fe |
completed | June 22, 2026, 4:16 a.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:07 p.m.