Triple
T34369516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taiwanese Canadians |
E882113
|
entity |
| Predicate | immigrationMotives |
P77259
|
FINISHED |
| Object | 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: education | Statement: [Taiwanese Canadians, immigrationMotives, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: immigrationMotives Context triple: [Taiwanese Canadians, immigrationMotives, education]
-
A.
immigrationReason
chosen
Indicates the reason or motivation behind an entity’s act of immigrating from one place to another.
-
B.
immigrationType
Indicates the specific category or classification of an individual’s immigration status or entry into a country.
-
C.
immigrationBackground
Indicates that an entity has a personal or familial history of migration from another country or region.
-
D.
immigrationDestinationFor
Indicates that a location serves as the destination to which an entity immigrates.
-
E.
immigrationFeature
Indicates that an entity possesses a characteristic, policy, or attribute specifically related to immigration.
- 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_69f349bf5d7481908dd5da4cbdf74047 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71c35327c8190884f1bfe12bd2cd7 |
completed | May 3, 2026, 9:58 a.m. |
| PD | Predicate disambiguation | batch_69f71822d0e88190ac9731c7ae5a4def |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 1:59 a.m.