Triple
T14531046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calhan, Colorado |
E340914
|
entity |
| Predicate | regionalEconomyActivity |
P114644
|
FINISHED |
| Object | cattle ranching |
—
|
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: cattle ranching | Statement: [Calhan, Colorado, regionalEconomyActivity, cattle ranching]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalEconomyActivity Context triple: [Calhan, Colorado, regionalEconomyActivity, cattle ranching]
-
A.
regionalEconomyType
Indicates the type or classification of an economy associated with a specific region.
-
B.
economicImpactRegion
Indicates the region or geographic area that experiences or is affected by a particular economic impact.
-
C.
economicArea
Indicates that one entity is part of, associated with, or falls under the jurisdiction of a defined economic region or zone of another entity.
-
D.
economicSectorSourceOfWealth
Indicates that a particular economic sector is the primary source from which an entity derives its wealth or income.
-
E.
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.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea052d01c81909c8592c351be6f35 |
completed | April 14, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c518fc08190a6ce4d8be05c4c5d |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de5fb5ac548190932f238e37271741 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:22 a.m.