Triple
T9484096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minnan language |
E228715
|
entity |
| Predicate | hasEducationStatus |
P70919
|
FINISHED |
| Object | taught in some schools in Taiwan |
—
|
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: taught in some schools in Taiwan | Statement: [Minnan language, hasEducationStatus, taught in some schools in Taiwan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationStatus Context triple: [Minnan language, hasEducationStatus, taught in some schools in Taiwan]
-
A.
educationStatus
Indicates the current or achieved level, stage, or condition of an entity’s formal education.
-
B.
hasStatusInEducation
chosen
Indicates that an entity holds a particular educational status or standing within an educational system, program, or institution.
-
C.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
D.
hasHigherEducationAccess
Indicates that one entity has access to higher education opportunities or institutions relative to another entity or context.
-
E.
hasEducationSetNumber
Indicates that an entity is associated with a specific numbered set or grouping of educational records or qualifications.
- 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_69ca84730a5081908de282651019bf2f |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd804e278c8190b1f869158075cd52 |
completed | April 1, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69cca561e6b0819090aa795f3c3a2083 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:55 p.m.