Triple

T8854879
Position Surface form Disambiguated ID Type / Status
Subject San José, Caldas E210729 entity
Predicate hasRuralLandscapeType P85002 FINISHED
Object coffee-growing rural landscape 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: coffee-growing rural landscape | Statement: [San José, Caldas, hasRuralLandscapeType, coffee-growing rural landscape]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasRuralLandscapeType
Context triple: [San José, Caldas, hasRuralLandscapeType, coffee-growing rural landscape]
  • A. hasRuralArea
    Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
  • B. hasRuralZoningCharacter
    Indicates that a property or area possesses zoning attributes and regulations typical of rural land use.
  • C. hasRuralHinterland
    Indicates that a place or urban area is associated with and served by a surrounding rural region that supports it economically, socially, or functionally.
  • D. isRural
    Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
  • E. hasRuralLocality
    Indicates that an entity possesses, includes, or is associated with a rural locality (such as a village, hamlet, or countryside settlement) within its scope or jurisdiction.
  • 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_69ca838a424c8190b1ecac115c2927e7 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60c6dce88190b175698b191fb89b completed April 1, 2026, 12:03 a.m.
PD Predicate disambiguation batch_69cc5c25b874819084c9ba391703e066 completed March 31, 2026, 11:43 p.m.
PDg Predicate description generation batch_69cc5cffe8ec819084c12770fe0578f2 completed March 31, 2026, 11:47 p.m.
Created at: March 30, 2026, 6:49 p.m.