Triple
T12474532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australia and United Kingdom |
E298141
|
entity |
| Predicate | hasMigrationLink |
P98061
|
FINISHED |
| Object | significant two-way 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: significant two-way migration | Statement: [Australia and United Kingdom, hasMigrationLink, significant two-way migration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMigrationLink Context triple: [Australia and United Kingdom, hasMigrationLink, significant two-way 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.
hasMigrationDimension
Indicates that there exists a relevant aspect or factor of migration associated with the subject in relation to the object.
-
D.
hasMigrationDriver
Indicates that one factor or condition serves as a driving cause or motivation for a migration event or process.
-
E.
hasMigrationAspect
chosen
Indicates that something possesses a characteristic, feature, or dimension specifically related to migration or migratory behavior.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.