Triple

T18044087
Position Surface form Disambiguated ID Type / Status
Subject Kevin M. Murphy E431726 entity
Predicate notableWork P4 FINISHED
Object “Wage Inequality and the Rise in Returns to Skill”
“Wage Inequality and the Rise in Returns to Skill” is an influential economics paper that analyzes how increasing wage gaps are driven by growing returns to education and skills in the labor market.
E1302676 NE FINISHED

How this triple was built (4 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: “Wage Inequality and the Rise in Returns to Skill” | Statement: [Kevin M. Murphy, notableWork, “Wage Inequality and the Rise in Returns to Skill”]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: “Wage Inequality and the Rise in Returns to Skill”
Context triple: [Kevin M. Murphy, notableWork, “Wage Inequality and the Rise in Returns to Skill”]
  • A. Tasks, Automation, and the Rise in US Wage Inequality
    "Tasks, Automation, and the Rise in US Wage Inequality" is an economics research paper analyzing how technological change and the automation of specific job tasks have contributed to growing wage inequality in the United States.
  • B. Schooling, Experience, and Earnings
    "Schooling, Experience, and Earnings" is a seminal work in labor economics that established the empirical foundations of human capital theory by analyzing how education and work experience affect individuals’ wages.
  • C. “Inequality in America: What Role for Human Capital Policies?”
    “Inequality in America: What Role for Human Capital Policies?” is an influential work by economist James Heckman that analyzes how investments in education and skills, especially early in life, can reduce economic inequality and improve long-term social outcomes in the United States.
  • D. Investment in Human Capital and Personal Income Distribution
    "Investment in Human Capital and Personal Income Distribution" is an influential economic study that analyzes how education and skill investments shape individuals’ earnings and the overall distribution of income.
  • E. Frisch elasticity of labor supply
    The Frisch elasticity of labor supply is an economic measure that captures how responsive individuals’ labor supply is to changes in wages when their expected lifetime wealth is held constant.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: “Wage Inequality and the Rise in Returns to Skill”
Triple: [Kevin M. Murphy, notableWork, “Wage Inequality and the Rise in Returns to Skill”]
Generated description
“Wage Inequality and the Rise in Returns to Skill” is an influential economics paper that analyzes how increasing wage gaps are driven by growing returns to education and skills in the labor market.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: “Wage Inequality and the Rise in Returns to Skill”
Target entity description: “Wage Inequality and the Rise in Returns to Skill” is an influential economics paper that analyzes how increasing wage gaps are driven by growing returns to education and skills in the labor market.
  • A. Tasks, Automation, and the Rise in US Wage Inequality
    "Tasks, Automation, and the Rise in US Wage Inequality" is an economics research paper analyzing how technological change and the automation of specific job tasks have contributed to growing wage inequality in the United States.
  • B. Schooling, Experience, and Earnings
    "Schooling, Experience, and Earnings" is a seminal work in labor economics that established the empirical foundations of human capital theory by analyzing how education and work experience affect individuals’ wages.
  • C. “Inequality in America: What Role for Human Capital Policies?”
    “Inequality in America: What Role for Human Capital Policies?” is an influential work by economist James Heckman that analyzes how investments in education and skills, especially early in life, can reduce economic inequality and improve long-term social outcomes in the United States.
  • D. Investment in Human Capital and Personal Income Distribution
    "Investment in Human Capital and Personal Income Distribution" is an influential economic study that analyzes how education and skill investments shape individuals’ earnings and the overall distribution of income.
  • E. Frisch elasticity of labor supply
    The Frisch elasticity of labor supply is an economic measure that captures how responsive individuals’ labor supply is to changes in wages when their expected lifetime wealth is held constant.
  • F. None of above. chosen

Provenance (5 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_69d8b906482481908183315b9ecf9994 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4bff13f488190993445769551c9c2 completed April 19, 2026, 11:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0349b8930c8190bbd871393b4b949e completed May 12, 2026, 3:39 p.m.
NEDg Description generation batch_6a034b0817408190817e4a3ee0003d57 completed May 12, 2026, 3:45 p.m.
NED2 Entity disambiguation (via description) batch_6a034bdf5c808190ac329e663e220f1b completed May 12, 2026, 3:48 p.m.
Created at: April 10, 2026, 10:25 a.m.