Triple
T5673342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Islam in Egypt |
E125026
|
entity |
| Predicate | hasLanguageOfPractice |
P65907
|
FINISHED |
| Object | Arabic |
—
|
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: Arabic | Statement: [Islam in Egypt, hasLanguageOfPractice, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfPractice Context triple: [Islam in Egypt, hasLanguageOfPractice, Arabic]
-
A.
hasClericalLanguage
Indicates that something is expressed using formal, religious, or church-related language or terminology.
-
B.
practicedLawIn
Indicates that a person engaged in the professional practice of law within a specified jurisdiction or location.
-
C.
hasLinguist
Indicates that an entity is associated with or possesses a linguist, typically as a member, employee, collaborator, or resource.
-
D.
hasOfficerLanguage
Indicates that an officer is able or authorized to communicate in a specified language.
-
E.
hasPracticeFields
Indicates that an entity possesses or is associated with one or more designated fields or areas used for practice activities.
- 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_69c008295c808190acfe78915e7d656a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c025303860819093e51f176babed71 |
completed | March 22, 2026, 5:21 p.m. |
| PD | Predicate disambiguation | batch_69c021bc3894819084f37d14ba4b2644 |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c0252e18988190a8f3aa0684c12fb8 |
completed | March 22, 2026, 5:21 p.m. |
Created at: March 22, 2026, 3:43 p.m.