Triple
T21985776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | وزارة النقل المصرية |
E542957
|
entity |
| Predicate | اللغة الرسمية |
P236
|
FINISHED |
| Object | اللغة العربية |
—
|
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: اللغة العربية | Statement: [وزارة النقل المصرية, اللغة الرسمية, اللغة العربية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: اللغة الرسمية Context triple: [وزارة النقل المصرية, اللغة الرسمية, اللغة العربية]
-
A.
officialLanguage
chosen
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
-
B.
languageOfOfficialAnnouncements
Indicates the language used for formal or official public announcements issued by an authority.
-
C.
shareOfficialLanguage
Indicates that two entities have at least one official language in common.
-
D.
laterOfficialLanguage
Indicates that one language became an official language of an entity at a later time than another language.
-
E.
previousOfficialLanguage
Indicates that one language formerly held official status in a country, region, or organization before being replaced or losing that status.
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12709cb288190a2620e337fea364c |
completed | April 28, 2026, 9:30 p.m. |
| PD | Predicate disambiguation | batch_69e6f6154e408190acc5b2c278acaff4 |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:04 p.m.