Triple

T19573838
Position Surface form Disambiguated ID Type / Status
Subject Southern Uzbekistan E489794 entity
Predicate agriculturalChallenge P125911 FINISHED
Object water scarcity 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: water scarcity | Statement: [Southern Uzbekistan, agriculturalChallenge, water scarcity]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: agriculturalChallenge
Context triple: [Southern Uzbekistan, agriculturalChallenge, water scarcity]
  • A. cultivationChallenge
    Indicates a situation where the process of cultivating or growing something faces difficulty, obstacles, or increased effort.
  • B. hasAgriculturalChallenge chosen
    Indicates that an entity is experiencing or associated with a difficulty, problem, or obstacle related to agriculture or farming activities.
  • C. agriculturalFocus
    Indicates that an entity is primarily concerned with, oriented toward, or specializing in agriculture or farming-related activities.
  • D. agriculturalPractice
    Indicates a relationship where an entity engages in, applies, or is associated with a specific method or technique of agriculture or farming.
  • E. agriculturalImplication
    Indicates a relationship where one factor, event, or condition has consequences, effects, or relevance specifically within an agricultural context.
  • 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_69d8e8dd9374819098e36349b3211663 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6402333dc8190bdffb1da68e2c76b completed April 20, 2026, 3:02 p.m.
PD Predicate disambiguation batch_69e514dbdb988190b55931a8138c73e7 completed April 19, 2026, 5:46 p.m.
Created at: April 10, 2026, 1:42 p.m.