Triple
T9941416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shuayb |
E194090
|
entity |
| Predicate | languageTraditionallyAssociated |
P11341
|
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: [Shuayb, languageTraditionallyAssociated, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageTraditionallyAssociated Context triple: [Shuayb, languageTraditionallyAssociated, Arabic]
-
A.
languageFamilyTraditional
Indicates that one entity belongs to, or is classified under, the traditional language family of the other entity.
-
B.
traditionalLanguageName
Indicates the name traditionally used in a particular language to refer to the subject entity.
-
C.
isCulturalLanguageOf
chosen
Indicates that a language serves as a primary medium of cultural expression, identity, and heritage for a particular group, community, or region.
-
D.
languageTraditions
Indicates that there is a relationship between entities involving the customs, practices, and conventions associated with the use, preservation, or transmission of a particular language.
-
E.
macrolanguageOf
Indicates that one language functions as a macrolanguage encompassing or grouping together one or more related individual languages.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb610905c81909d669265c92021a5 |
completed | April 2, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9428cc81909b4b4938566d78a7 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:44 p.m.