Triple
T22191153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhutanese American |
E548427
|
entity |
| Predicate | majorMigrationReason |
P134391
|
FINISHED |
| Object | refugee resettlement |
—
|
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: refugee resettlement | Statement: [Bhutanese American, majorMigrationReason, refugee resettlement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorMigrationReason Context triple: [Bhutanese American, majorMigrationReason, refugee resettlement]
-
A.
migrationCause
Indicates the reason or driving factor that leads an entity to migrate from one place to another.
-
B.
reasonForRelocation
Indicates the underlying cause, motivation, or circumstance that led an entity to move from one location to another.
-
C.
reasonForChange
Indicates that one entity serves as the cause, justification, or motivation for a modification or change in another entity or state.
-
D.
verticalMigration
Indicates movement of an entity up and down along a vertical axis, typically in a repeated or cyclical pattern over time.
-
E.
hasReasonForMigration
chosen
Indicates that there exists a specific cause, motive, or justification for an entity’s act of migrating from one place to another.
- 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_69e11e3e0c7c8190b30d278845e2497e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12ae3e8148190a23decd2dfe24e28 |
completed | April 28, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69e71b48576c8190a8e93738fd9cfda5 |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:35 p.m.