Triple
T304037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monroe, Louisiana |
E6258
|
entity |
| Predicate | isRegionalHubFor |
P9422
|
FINISHED |
| Object | commerce |
—
|
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: commerce | Statement: [Monroe, Louisiana, isRegionalHubFor, commerce]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRegionalHubFor Context triple: [Monroe, Louisiana, isRegionalHubFor, commerce]
-
A.
primaryHubFor
Indicates that one entity serves as the main central hub or core point of coordination for another entity or set of entities.
-
B.
isCommercialHubIn
chosen
Indicates that a place functions as a primary center of commercial or business activity within a specified larger area or region.
-
C.
isRailHubFor
Indicates that a location functions as a central node or interchange point within a rail network for the referenced area, routes, or services.
-
D.
isResidentialHubIn
Indicates that a location functions primarily as a residential center or hub within a specified larger area or region.
-
E.
isCentralTo
Indicates that something plays a primary, essential, or defining role in relation to something else, such that the latter depends on or is organized around it.
- 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_69a2e79230508190b912ecb555aae17e |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea1032e48190864338e030d9dc92 |
completed | Feb. 28, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69a2e93db11881909b07ba5e76d91feb |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.