Triple
T30746064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalimat-i-Maknúnih |
E782818
|
entity |
| Predicate | sectionLanguage |
P31857
|
FINISHED |
| Object | Arabic section |
—
|
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 section | Statement: [Kalimat-i-Maknúnih, sectionLanguage, Arabic section]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectionLanguage Context triple: [Kalimat-i-Maknúnih, sectionLanguage, Arabic section]
-
A.
navigationLanguage
Indicates the language used for navigation-related content, such as menus, directions, or interface controls.
-
B.
suffixLanguage
Indicates that one language is used as a suffix or ending element in the formation or representation of another language or linguistic expression.
-
C.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
-
D.
contentLanguage
chosen
Indicates the language in which the content is expressed or intended to be understood.
-
E.
languageSubject
Indicates that a particular language is the subject or topic being studied, discussed, or otherwise focused on in relation to another entity.
- 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_69f224af8d8481908bea03890c5618be |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f68f6d7784819088186ac39e29c919 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f686140aa08190a35f62572b2db9b6 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:38 p.m.