Triple
T19212352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wright City, Missouri |
E480385
|
entity |
| Predicate | regionalEconomyIncludes |
P114644
|
FINISHED |
| Object | logistics and warehousing |
—
|
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: logistics and warehousing | Statement: [Wright City, Missouri, regionalEconomyIncludes, logistics and warehousing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalEconomyIncludes Context triple: [Wright City, Missouri, regionalEconomyIncludes, logistics and warehousing]
-
A.
regionalEconomyType
Indicates the type or classification of an economy associated with a specific region.
-
B.
regionalEconomyActivity
chosen
Indicates the type or level of economic activity occurring within a specific geographic region.
-
C.
economicArea
Indicates that one entity is part of, associated with, or falls under the jurisdiction of a defined economic region or zone of another entity.
-
D.
economicImpactRegion
Indicates the region or geographic area that experiences or is affected by a particular economic impact.
-
E.
servesEconomicRegion
Indicates that an entity provides services, support, or functions that benefit or are directed toward a particular economic region.
- 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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa37fc7881908c53e332625dcdb4 |
completed | April 20, 2026, 10:04 a.m. |
| PD | Predicate disambiguation | batch_69e4dcf22b3c8190bee02e3af946e114 |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:21 p.m.