Triple
T31471130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | southern Cairo metropolitan area |
E802861
|
entity |
| Predicate | dialectMajority |
P24988
|
FINISHED |
| Object | Egyptian Arabic |
—
|
NE NERFINISHED |
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: Egyptian Arabic | Statement: [southern Cairo metropolitan area, dialectMajority, Egyptian Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dialectMajority Context triple: [southern Cairo metropolitan area, dialectMajority, Egyptian Arabic]
-
A.
majorDialectOf
Indicates that one dialect is the primary or most prominent dialect associated with a particular language or region.
-
B.
dominantDialect
chosen
Indicates that one dialect is the primary or most influential form of a language within a particular context or region.
-
C.
majorityLanguageOf
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or entity.
-
D.
majoritySpokenOn
Indicates that a language is the primary or most commonly spoken language within a specified region, group, or context.
-
E.
languageFamilyDominant
Indicates that one language family holds a primary or prevailing status over others within a given context (such as a region, population, or system).
- 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_69f348c84c1c81908739f100ecf7394e |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 30, 2026, 9:26 p.m.