Triple
T2488578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dhuandhar Falls |
E55985
|
entity |
| Predicate | localEconomyImpact |
P40344
|
FINISHED |
| Object | supports local tourism-related 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: supports local tourism-related businesses | Statement: [Dhuandhar Falls, localEconomyImpact, supports local tourism-related businesses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localEconomyImpact Context triple: [Dhuandhar Falls, localEconomyImpact, supports local tourism-related businesses]
-
A.
economicImpactRegion
Indicates the region or geographic area that experiences or is affected by a particular economic impact.
-
B.
regionalEconomyType
Indicates the type or classification of an economy associated with a specific region.
-
C.
covid19Impact
Indicates the effect, consequences, or influence that COVID-19 has on a given entity, condition, or situation.
-
D.
economicFunction
Indicates the role or purpose an entity serves within an economic system, such as how it contributes to production, distribution, or consumption of goods and services.
-
E.
hasTourismImpactOn
Indicates that one entity affects or influences the tourism levels, patterns, or attractiveness of another entity.
- F. None of above. chosen
Provenance (4 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b7cf088190bcff4dac6150044c |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd209d934819093600889af9104c3 |
completed | March 7, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:45 p.m.