Triple
T23736458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saudi judiciary |
E586552
|
entity |
| Predicate | appliesPersonalStatusLawTo |
P153468
|
FINISHED |
| Object | marriage |
—
|
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: marriage | Statement: [Saudi judiciary, appliesPersonalStatusLawTo, marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesPersonalStatusLawTo Context triple: [Saudi judiciary, appliesPersonalStatusLawTo, marriage]
-
A.
hasCivilStatus
Indicates the civil or marital status that applies to a person or entity (e.g., single, married, divorced).
-
B.
usedLegalStatus
Indicates that one entity applies or relies on the legal status or classification of another entity in a given context.
-
C.
civicStatus
Indicates the legal or social standing of an individual within a civic or societal framework, such as marital or citizenship status.
-
D.
marriageLegalStatus
Indicates the legal status of a marriage relationship between entities, such as whether it is valid, invalid, pending, or dissolved under applicable law.
-
E.
legalStatusRecognizedIn
Indicates that an entity’s legal status is officially acknowledged or valid within a specified jurisdiction or legal system.
- 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_69e24907dc9c8190be074c9c96a0ec2d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bad28fa481909d7a6a6e98a7b0a5 |
completed | April 29, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
| PDg | Predicate description generation | batch_69f15adb23d88190ac2632299c26a9b3 |
completed | April 29, 2026, 1:11 a.m. |
Created at: April 17, 2026, 7:10 p.m.