Triple
T8166728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trasianka |
E190710
|
entity |
| Predicate | typicalDomainOfUse |
P24492
|
FINISHED |
| Object | informal communication |
—
|
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: informal communication | Statement: [Trasianka, typicalDomainOfUse, informal communication]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDomainOfUse Context triple: [Trasianka, typicalDomainOfUse, informal communication]
-
A.
typicalDomain
chosen
Indicates that one entity is the characteristic or most common domain, context, or area of application in which another entity typically occurs or is used.
-
B.
usedInDomain
Indicates that something (such as a concept, method, or resource) is applied or utilized within a particular domain or field.
-
C.
typicalSectorUse
Indicates the type of sector in which something is most commonly or characteristically used.
-
D.
appliesPrimarilyTo
Indicates that a property, rule, or characteristic is mainly relevant or intended for a particular entity or group, more than for others.
-
E.
primarilyUsedBy
Indicates that something is mainly or most commonly used by a particular entity or group.
- 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_69ca82c0ef14819083713f4473dd847c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb46680fac81908df134df9bf84915 |
completed | March 31, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69cb36a4c40c81909f60aef0e1624c13 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:39 p.m.