Triple
T32179802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkmen American |
E821948
|
entity |
| Predicate | typicalMigrationReason |
P42539
|
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: [Turkmen American, typicalMigrationReason, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMigrationReason Context triple: [Turkmen American, typicalMigrationReason, education]
-
A.
reasonForRelocation
Indicates the underlying cause, motivation, or circumstance that led an entity to move from one location to another.
-
B.
migrationCause
chosen
Indicates the reason or driving factor that leads an entity to migrate from one place to another.
-
C.
immigrationReason
Indicates the reason or motivation behind an entity’s act of immigrating from one place to another.
-
D.
typicalMigrationStatus
Indicates the usual or characteristic migration state or pattern associated with an entity.
-
E.
citizenshipChangeReason
Indicates the reason or cause for a change in an entity’s citizenship status.
- 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_69f3490755288190aee11740a34862f9 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379eaa540819095a1c5d9f3513f9b |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:34 a.m.