Triple
T16934664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | qadis |
E410796
|
entity |
| Predicate | historicalLanguageOfOffice |
P11893
|
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: [qadis, historicalLanguageOfOffice, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalLanguageOfOffice Context triple: [qadis, historicalLanguageOfOffice, Arabic]
-
A.
previousOfficialLanguage
Indicates that one language formerly held official status in a country, region, or organization before being replaced or losing that status.
-
B.
historicallyDominantLanguageOfAdministrationIn
chosen
Indicates that a language has historically been the primary language used for official governance and administrative functions within a given place or political entity.
-
C.
officialLanguage
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.
-
D.
laterOfficialLanguage
Indicates that one language became an official language of an entity at a later time than another language.
-
E.
hasLanguageOfOfficialName
Indicates that an entity’s official name is expressed in a specified language.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cf2899608190a6bacdce9d4ceb84 |
completed | April 18, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b982f548190b08414d55810de19 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:30 a.m.