Triple
T3758226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MSA |
E82098
|
entity |
| Predicate | usageTrend |
P5318
|
FINISHED |
| Object | dominant in written communication in the Arab world |
—
|
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: dominant in written communication in the Arab world | Statement: [MSA, usageTrend, dominant in written communication in the Arab world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usageTrend Context triple: [MSA, usageTrend, dominant in written communication in the Arab world]
-
A.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
B.
usagePattern
Indicates how something is typically used or the recurring manner in which it is employed or consumed.
-
C.
hasTrend
chosen
Indicates that something exhibits or is associated with a particular pattern of change or direction over time.
-
D.
trends
Indicates that one entity exhibits a general direction of change or development over time in relation to another reference or context.
-
E.
usagePeak
Indicates that the usage or consumption of something reaches its highest level or intensity during a particular time or condition.
- 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.