Triple
T174876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sun Belt |
E3553
|
entity |
| Predicate | economicTrend |
P7393
|
FINISHED |
| Object | shift from manufacturing to services |
—
|
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: shift from manufacturing to services | Statement: [Sun Belt, economicTrend, shift from manufacturing to services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicTrend Context triple: [Sun Belt, economicTrend, shift from manufacturing to services]
-
A.
economicAspect
Indicates that something is related to, characterized by, or has implications for economic factors, conditions, or outcomes.
-
B.
economicUse
Indicates that one entity utilizes another for economic purposes, such as production, trade, revenue generation, or cost-saving activities.
-
C.
economicSystem
Indicates the type or structure of the economic organization or system under which an entity operates or to which it belongs.
-
D.
economicClassification
Indicates how an entity is categorized based on its economic characteristics, status, or role within an economic system.
-
E.
sector
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a258e32da88190ad9485aecd0bf08f |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a25669d99481908c5e82ba8641205a |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a258b30f6c8190be2181f30c40e04d |
completed | Feb. 28, 2026, 2:53 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.