Triple

T38299647
Position Surface form Disambiguated ID Type / Status
Subject Piriyapatna E1032186 entity
Predicate hasAgricultureActivity P25683 FINISHED
Object coffee cultivation 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 cultivation | Statement: [Piriyapatna, hasAgricultureActivity, coffee cultivation]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAgricultureActivity
Context triple: [Piriyapatna, hasAgricultureActivity, coffee cultivation]
  • A. hasAgriculturalProduction chosen
    Indicates that an entity engages in or is characterized by the production of agricultural goods such as crops or livestock.
  • B. hasAgriculturalCharacter
    Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
  • C. hasAgriculturalFacility
    Indicates that an entity possesses, contains, or is associated with an agricultural facility used for farming, cultivation, or related agricultural operations.
  • D. hasAgriculturalType
    Indicates that an entity is associated with or classified by a specific type or category of agriculture.
  • E. hasNearbyAgriculturalActivity
    Indicates that an entity is located close enough to agricultural operations or land use for those activities to be considered relevant or influential to it.
  • 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_69f76e0f2084819091299d021625c3fe completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fccbd826708190b5fab12c4236299a completed May 7, 2026, 5:28 p.m.
PD Predicate disambiguation batch_69fcc58838e08190b8fa54aa5c165f2d completed May 7, 2026, 5:02 p.m.
Created at: May 3, 2026, 4:30 p.m.