Triple
T25967997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | جيبوتي |
E645726
|
entity |
| Predicate | الكتابة_باللغات_الرسمية |
P17914
|
FINISHED |
| Object | العربية والفرنسية في الوثائق الرسمية |
—
|
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: العربية والفرنسية في الوثائق الرسمية | Statement: [جيبوتي, الكتابة_باللغات_الرسمية, العربية والفرنسية في الوثائق الرسمية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: الكتابة_باللغات_الرسمية Context triple: [جيبوتي, الكتابة_باللغات_الرسمية, العربية والفرنسية في الوثائق الرسمية]
-
A.
languageOfOfficialReports
Indicates the language in which an entity’s official reports are written or issued.
-
B.
languageOfWritings
chosen
Indicates that a specified language is the one in which certain writings or written works are composed.
-
C.
languageOfOfficialAnnouncements
Indicates the language used for formal or official public announcements issued by an authority.
-
D.
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.
-
E.
languageOfLetters
Indicates that one entity is the language in which the other entity’s letters or written correspondence are composed.
- 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_69e77e8768648190b27bb578f14bcb88 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f604cc423081908edb1fcf694f06fc |
completed | May 2, 2026, 2:06 p.m. |
| PD | Predicate disambiguation | batch_69f4a10480748190a2e67bd399fc435d |
completed | May 1, 2026, 12:48 p.m. |
Created at: April 22, 2026, 8:50 a.m.