Triple
T20043487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentina and Paraguay |
E497490
|
entity |
| Predicate | haveMigrationFlows |
P138473
|
FINISHED |
| Object | cross-border migration |
—
|
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: cross-border migration | Statement: [Argentina and Paraguay, haveMigrationFlows, cross-border migration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveMigrationFlows Context triple: [Argentina and Paraguay, haveMigrationFlows, cross-border migration]
-
A.
hasMigrationTo
Indicates a directed movement or transfer from one place, system, or state to another.
-
B.
hasMigrationHistoryFrom
Indicates that an entity has a recorded history of migrating or moving from a specified origin location or source.
-
C.
hasMigrationIssue
Indicates that an entity experiences a problem, error, or complication during a migration process from one system, environment, or version to another.
-
D.
hasMigrationAspect
Indicates that something possesses a characteristic, feature, or dimension specifically related to migration or migratory behavior.
-
E.
hasMigrationDimension
Indicates that there exists a relevant aspect or factor of migration associated with the subject in relation to the object.
- F. None of above. chosen
Provenance (4 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662ed59bc8190a9ff25493e500ebb |
completed | April 20, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:37 p.m.