Triple
T32903080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Korean migrant workers in West Germany |
E841661
|
entity |
| Predicate | migrationMotivations |
P77259
|
FINISHED |
| Object | economic opportunity |
—
|
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: economic opportunity | Statement: [South Korean migrant workers in West Germany, migrationMotivations, economic opportunity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: migrationMotivations Context triple: [South Korean migrant workers in West Germany, migrationMotivations, economic opportunity]
-
A.
migrationCause
Indicates the reason or driving factor that leads an entity to migrate from one place to another.
-
B.
immigrationReason
chosen
Indicates the reason or motivation behind an entity’s act of immigrating from one place to another.
-
C.
migrationImportance
Indicates the degree to which something is significant, critical, or prioritized within a migration process or transition.
-
D.
migration
Indicates the movement of entities from one location or context to another, often across boundaries or over time.
-
E.
reasonForRelocation
Indicates the underlying cause, motivation, or circumstance that led an entity to move from one location 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_69f34946a5208190bbd79f0fec4323bd |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d16f5cb881908eed141afaaa0b51 |
completed | May 3, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 1:19 a.m.