Triple
T36305087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sui people of Guizhou |
E893922
|
entity |
| Predicate | migrationTrend |
P39078
|
FINISHED |
| Object | increasing labor migration to urban centers in recent decades |
—
|
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: increasing labor migration to urban centers in recent decades | Statement: [Sui people of Guizhou, migrationTrend, increasing labor migration to urban centers in recent decades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: migrationTrend Context triple: [Sui people of Guizhou, migrationTrend, increasing labor migration to urban centers in recent decades]
-
A.
directionOfMigration
Indicates the geographic direction or path along which a migration movement proceeds from its origin toward its destination.
-
B.
migration
Indicates the movement of entities from one location or context to another, often across boundaries or over time.
-
C.
areaTrend
Indicates how the size or spatial extent of something changes over time or across conditions.
-
D.
migrationImpact
Indicates how migration influences or changes conditions, outcomes, or states within a given context.
-
E.
trends
chosen
Indicates that one entity exhibits a general direction of change or development over time in relation to another reference or context.
- 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_69f76e4c1b248190b10667d0213537fe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7ba6d06f48190a71b5a2f19e2232f |
completed | May 3, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.