Triple
T37445571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nove Colli |
E930534
|
entity |
| Predicate | localEconomicImpact |
P40344
|
FINISHED |
| Object | tourism and hospitality in Cesenatico |
—
|
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: tourism and hospitality in Cesenatico | Statement: [Nove Colli, localEconomicImpact, tourism and hospitality in Cesenatico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localEconomicImpact Context triple: [Nove Colli, localEconomicImpact, tourism and hospitality in Cesenatico]
-
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.
partOfLocalEconomy
Indicates that an entity contributes to, participates in, or is integrated within the economic activities of a specific local area or community.
-
C.
economicImpactRegion
Indicates the region or geographic area that experiences or is affected by a particular economic impact.
-
D.
impactOnEconomy
Indicates the effect or influence that one factor, event, or action has on the state or performance of an economy.
-
E.
regionalEconomyActivity
Indicates the type or level of economic activity occurring within a specific geographic 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_69f76ec0b9488190b7a4fae632bd1d2f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:17 p.m.