Triple
T477010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Middle Eastern American |
E9082
|
entity |
| Predicate | hasMigrationPattern |
P4575
|
FINISHED |
| Object | immigration to the United States |
—
|
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: immigration to the United States | Statement: [Middle Eastern American, hasMigrationPattern, immigration to the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMigrationPattern Context triple: [Middle Eastern American, hasMigrationPattern, immigration to the United States]
-
A.
hasMigrationHistoryFrom
Indicates that an entity has a recorded history of migrating or moving from a specified origin location or source.
-
B.
migrationPattern
chosen
Indicates the typical routes, timing, and destinations followed by entities as they move periodically from one location or region to another.
-
C.
hasPattern
Indicates that one entity exhibits, follows, or is characterized by a specific recurring form, structure, or design defined by another entity.
-
D.
associatedWithMigrationType
Indicates that one entity has a specified connection or linkage to a particular type or category of migration.
-
E.
hasDatabase
Indicates that an entity possesses, uses, or is associated with a specific database.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f03cc63881908e75b457804cb858 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edf017548190ae38ff3314a1ffa3 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.