Triple

T12152833
Position Surface form Disambiguated ID Type / Status
Subject Kalpasar project E289499 entity
Predicate potentialBenefit P49949 FINISHED
Object increase irrigation coverage in Saurashtra 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: increase irrigation coverage in Saurashtra | Statement: [Kalpasar project, potentialBenefit, increase irrigation coverage in Saurashtra]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: potentialBenefit
Context triple: [Kalpasar project, potentialBenefit, increase irrigation coverage in Saurashtra]
  • A. expectedBenefit chosen
    Indicates the benefit or positive outcome that is anticipated to result from a particular action, decision, or relationship between entities.
  • B. benefice
    Indicates that one entity grants or bestows a benefit, favor, or advantage upon another.
  • C. benefits
    Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
  • D. believedBenefit
    Indicates that one entity considers or perceives another entity, action, or state as providing an advantage or positive outcome.
  • E. primaryBenefit
    Indicates that one entity serves as the main or most important advantage, gain, or positive outcome associated with another entity.
  • 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915d7109481908bf5fe512bba3c89 completed April 10, 2026, 3:23 p.m.
PD Predicate disambiguation batch_69d9150c18148190bf8152189c0e5fca completed April 10, 2026, 3:19 p.m.
Created at: April 8, 2026, 9:49 p.m.