Triple

T3707475
Position Surface form Disambiguated ID Type / Status
Subject Vilfredo Pareto E80927 entity
Predicate knownFor P22 FINISHED
Object Pareto efficiency E145374 NE 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: Pareto efficiency | Statement: [Vilfredo Pareto, knownFor, Pareto efficiency]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pareto efficiency
Context triple: [Vilfredo Pareto, knownFor, Pareto efficiency]
  • A. Pareto efficiency chosen
    Pareto efficiency is an economic concept describing an allocation of resources where no individual can be made better off without making someone else worse off.
  • B. Hicks–Kaldor compensation criterion
    The Hicks–Kaldor compensation criterion is an economic efficiency test stating that a policy change is desirable if those who gain could in principle compensate those who lose and still be better off, regardless of whether compensation actually occurs.
  • C. On Equilibrium
    On Equilibrium is a philosophical work by John Ralston Saul that explores the importance of balancing key human qualities—such as reason, ethics, and common sense—to create a more humane and democratic society.
  • D. Walrasian market-clearing framework
    The Walrasian market-clearing framework is a general equilibrium model in which perfectly competitive markets continuously adjust prices so that supply equals demand in all markets simultaneously.
  • E. Karush–Kuhn–Tucker conditions
    The Karush–Kuhn–Tucker conditions are fundamental optimality criteria in nonlinear programming that generalize Lagrange multipliers to handle inequality constraints.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ad8b1793888190a5f70e4b21dc05a1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc57edd748190a006e15fa0248679 completed March 8, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4ce0216bc8190b44d2950b7cb24c3 completed March 14, 2026, 2:54 a.m.
Created at: March 8, 2026, 3:33 p.m.