Triple
T3758292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fus’ha |
E82099
|
entity |
| Predicate | roleInDiglossia |
P7163
|
FINISHED |
| Object | high variety in Arabic diglossia |
—
|
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: high variety in Arabic diglossia | Statement: [Fus’ha, roleInDiglossia, high variety in Arabic diglossia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInDiglossia Context triple: [Fus’ha, roleInDiglossia, high variety in Arabic diglossia]
-
A.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
-
B.
roleInDialogue
Indicates that an entity participates in a dialogue with a specific conversational role (e.g., speaker, listener, moderator) relative to other participants.
-
C.
languageStandardizationRole
Indicates the role an entity plays in establishing, maintaining, or influencing the standardization of a language.
-
D.
sociolinguisticStatus
chosen
Indicates the social and cultural standing or prestige associated with a language variety or linguistic feature within a particular community or context.
-
E.
roleInAddressing
Indicates the specific function or responsibility an entity has in dealing with or responding to a particular issue, situation, or task.
- 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbc04d348190b0e4a90d18bdd160 |
completed | March 8, 2026, 7:19 p.m. |
| PD | Predicate disambiguation | batch_69adc04c851c8190ae5eaebf36df539b |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.