Triple
T1625187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southwestern Mandarin |
E35123
|
entity |
| Predicate | usageDomain |
P1248
|
FINISHED |
| Object | everyday spoken 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: everyday spoken communication | Statement: [Southwestern Mandarin, usageDomain, everyday spoken communication]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usageDomain Context triple: [Southwestern Mandarin, usageDomain, everyday spoken communication]
-
A.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
B.
usedInDomain
chosen
Indicates that something (such as a concept, method, or resource) is applied or utilized within a particular domain or field.
-
C.
scopeOfUse
Indicates the range, context, or conditions under which something is intended, allowed, or applicable to be used.
-
D.
designationUsedFor
Indicates that a particular name, label, or title is employed to refer to or identify a specific entity or role.
-
E.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized 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_69a886023194819080a3fccd6e325d0e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9431af5ac8190893133f1ae490142 |
completed | March 5, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69a907c91c888190b6ed295c1a2e0977 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.