Triple
T4970400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Llanfair Caereinion |
E111633
|
entity |
| Predicate | hasLocalEconomyFeature |
P52901
|
FINISHED |
| Object | small independent businesses |
—
|
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: small independent businesses | Statement: [Llanfair Caereinion, hasLocalEconomyFeature, small independent businesses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalEconomyFeature Context triple: [Llanfair Caereinion, hasLocalEconomyFeature, small independent businesses]
-
A.
hasEconomyCharacteristic
chosen
Indicates that an economy possesses a particular attribute, feature, or quality.
-
B.
localEconomyImpact
Indicates the effect that an action, event, or entity has on the economic conditions, activities, or performance of a specific local area or community.
-
C.
regionalEconomyType
Indicates the type or classification of an economy associated with a specific region.
-
D.
hasNearbyEconomicRegion
Indicates that one economic region is geographically close to or adjacent to another economic region.
-
E.
isEconomicCenter
Indicates that an entity functions as a primary hub for economic activity, such as trade, finance, or industry, within a region or system.
- 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_69bd441a0eb481908050fa4273b19eae |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd7146e6e881908a55ab2756b631f6 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:33 p.m.