Triple
T12384929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rupsha River |
E295837
|
entity |
| Predicate | hasLocalEconomyDependence |
P40344
|
FINISHED |
| Object | river transport |
—
|
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: river transport | Statement: [Rupsha River, hasLocalEconomyDependence, river transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalEconomyDependence Context triple: [Rupsha River, hasLocalEconomyDependence, river transport]
-
A.
localEconomyImpact
chosen
Indicates the effect that an action, event, or entity has on the economic conditions, activities, or performance of a specific local area or community.
-
B.
hasNearbyEconomicRegion
Indicates that one economic region is geographically close to or adjacent to another economic region.
-
C.
hasEconomyCharacteristic
Indicates that an economy possesses a particular attribute, feature, or quality.
-
D.
hasEconomicZoneImplication
Indicates that a relationship or action has consequences for the definition, use, rights, or regulations of an economic zone.
-
E.
hasEconomicOrganization
Indicates that an entity possesses, is associated with, or participates in a specific economic organization or institutional economic structure.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fbc3f608190b0ee3c4f304a94db |
completed | April 10, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69d93ed256788190b704cad171a4824e |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.