Triple

T1968147
Position Surface form Disambiguated ID Type / Status
Subject Inequality-adjusted Human Development Index E42735 entity
Predicate adjustmentMethod P6679 FINISHED
Object uses Atkinson inequality measure 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: uses Atkinson inequality measure | Statement: [Inequality-adjusted Human Development Index, adjustmentMethod, uses Atkinson inequality measure]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: adjustmentMethod
Context triple: [Inequality-adjusted Human Development Index, adjustmentMethod, uses Atkinson inequality measure]
  • A. adjustmentType
    Indicates the specific kind or category of modification applied to an existing value, state, or configuration within the relationship.
  • B. tuningMethod
    Indicates the method or approach used to adjust or optimize something’s parameters or performance.
  • C. divisorAdjustment
    Indicates an operation or relationship where a value is modified based on a divisor, typically scaling or normalizing it according to that divisor.
  • D. weightingMethod chosen
    Indicates how relative importance or influence is assigned to elements within a set, such as criteria, features, or data points, in a calculation or decision process.
  • E. notAdjustedFor
    Indicates that a value, measure, or result has not been modified or corrected to account for certain factors, conditions, or variables.
  • 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_69a88711151c8190940b2572095059d7 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb3cf15048190a51f73ed85e1b958 completed March 7, 2026, 5:12 a.m.
PD Predicate disambiguation batch_69abaff7d4a48190ab0d51aefb1c4e31 completed March 7, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:36 p.m.