Triple
T7946009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tujia language |
E184498
|
entity |
| Predicate | notCommonlyUsedInDomain |
P7974
|
FINISHED |
| Object | formal education |
—
|
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: formal education | Statement: [Tujia language, notCommonlyUsedInDomain, formal education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notCommonlyUsedInDomain Context triple: [Tujia language, notCommonlyUsedInDomain, formal education]
-
A.
notTypicallyUsedFor
chosen
Indicates that something is generally not used for a particular purpose, function, or activity under normal circumstances.
-
B.
usedInDomain
Indicates that something (such as a concept, method, or resource) is applied or utilized within a particular domain or field.
-
C.
notationDomain
Indicates a relationship where a notation system is associated with, or defined over, a particular domain in which it is valid or applicable.
-
D.
oftenUsedAsNameFor
Indicates that something frequently serves as a name or designation for another entity.
-
E.
isLessCommonThan
Indicates that one item occurs, appears, or is observed less frequently than another item.
- 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_69ca8291c2008190b1b8832c87814bcf |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b29a570819091a2ac185a8d57c4 |
completed | March 31, 2026, 3:10 a.m. |
| PD | Predicate disambiguation | batch_69cae93526d081909303265bf60419fd |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:09 p.m.