Triple
T25814358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | الروضة الشريفة |
E650207
|
entity |
| Predicate | hasGenderSpecificTimes |
P49314
|
FINISHED |
| Object | أوقات مخصصة للنساء |
—
|
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: أوقات مخصصة للنساء | Statement: [الروضة الشريفة, hasGenderSpecificTimes, أوقات مخصصة للنساء]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderSpecificTimes Context triple: [الروضة الشريفة, hasGenderSpecificTimes, أوقات مخصصة للنساء]
-
A.
hasGenderDivisions
chosen
Indicates that something is organized, classified, or separated into groups based on gender.
-
B.
hasGenderConvention
Indicates that there is an established or customary way of assigning or expressing gender within a given context, system, or culture.
-
C.
hasGenderPractice
Indicates a relationship where an entity engages in, follows, or applies a particular gender-related practice, norm, or behavior.
-
D.
hasNumberOfGenders
Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
-
E.
hasGenderVariant
Indicates that one entity is a gender-specific form or variant of another entity.
- 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_69e7ab35d264819095367f7e80c983ff |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 22, 2026, 7:12 a.m.