Triple
T14032809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | القوات الجوية والدفاع الجوي |
E337633
|
entity |
| Predicate | تستخدم_لغة |
P18209
|
FINISHED |
| Object | اللغة الإنجليزية في الاتصالات الجوية |
—
|
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 الإنجليزية في الاتصالات الجوية | Statement: [القوات الجوية والدفاع الجوي, تستخدم_لغة, اللغة الإنجليزية في الاتصالات الجوية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تستخدم_لغة Context triple: [القوات الجوية والدفاع الجوي, تستخدم_لغة, اللغة الإنجليزية في الاتصالات الجوية]
-
A.
usesLanguageFor
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
-
B.
languageUse
chosen
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
C.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
D.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
E.
usesLanguageAs
Indicates that one entity communicates or operates using another entity as its language or linguistic medium.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fab17008190981f1808726fa11c |
completed | April 14, 2026, 12:14 p.m. |
| PD | Predicate disambiguation | batch_69de05ab36b48190920efb1869bdb1fe |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:20 p.m.