Triple
T8800341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Craig Kielburger |
E209389
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
WEconomy: You Can Find Meaning, Make A Living, and Change the World
WEconomy: You Can Find Meaning, Make A Living, and Change the World is a business and social impact book that guides readers on integrating purpose and profit to build careers and companies that create positive global change.
|
E759279
|
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: WEconomy: You Can Find Meaning, Make A Living, and Change the World | Statement: [Craig Kielburger, notableWork, WEconomy: You Can Find Meaning, Make A Living, and Change the World]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WEconomy: You Can Find Meaning, Make A Living, and Change the World Context triple: [Craig Kielburger, notableWork, WEconomy: You Can Find Meaning, Make A Living, and Change the World]
-
A.
There Is Nothing for You Here: Finding Opportunity in the Twenty-First Century
"There Is Nothing for You Here: Finding Opportunity in the Twenty-First Century" is a political memoir and analysis by foreign policy expert Fiona Hill, exploring economic decline, populism, and the search for opportunity through her experiences in the UK, Russia, and the United States.
-
B.
Deep Economy
Deep Economy is a nonfiction book by environmentalist Bill McKibben that critiques growth-driven economics and advocates for more localized, sustainable, and community-centered alternatives.
-
C.
Economics for the Common Good
Economics for the Common Good is a book by Nobel laureate Jean Tirole that explains how modern economic thinking can be used to address major social challenges and improve public policy.
-
D.
Good Economics for Hard Times
Good Economics for Hard Times is a popular economics book by Nobel laureates Abhijit V. Banerjee and Esther Duflo that examines contemporary social and economic challenges through rigorous empirical research and accessible analysis.
-
E.
American Made: What Happens to People When Work Disappears
American Made: What Happens to People When Work Disappears is a nonfiction book that examines the human and community consequences of deindustrialization and job loss in the United States through the stories of displaced factory workers.
- 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: WEconomy: You Can Find Meaning, Make A Living, and Change the World Triple: [Craig Kielburger, notableWork, WEconomy: You Can Find Meaning, Make A Living, and Change the World]
Generated description
WEconomy: You Can Find Meaning, Make A Living, and Change the World is a business and social impact book that guides readers on integrating purpose and profit to build careers and companies that create positive global change.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: WEconomy: You Can Find Meaning, Make A Living, and Change the World Target entity description: WEconomy: You Can Find Meaning, Make A Living, and Change the World is a business and social impact book that guides readers on integrating purpose and profit to build careers and companies that create positive global change.
-
A.
There Is Nothing for You Here: Finding Opportunity in the Twenty-First Century
"There Is Nothing for You Here: Finding Opportunity in the Twenty-First Century" is a political memoir and analysis by foreign policy expert Fiona Hill, exploring economic decline, populism, and the search for opportunity through her experiences in the UK, Russia, and the United States.
-
B.
Deep Economy
Deep Economy is a nonfiction book by environmentalist Bill McKibben that critiques growth-driven economics and advocates for more localized, sustainable, and community-centered alternatives.
-
C.
Economics for the Common Good
Economics for the Common Good is a book by Nobel laureate Jean Tirole that explains how modern economic thinking can be used to address major social challenges and improve public policy.
-
D.
Good Economics for Hard Times
Good Economics for Hard Times is a popular economics book by Nobel laureates Abhijit V. Banerjee and Esther Duflo that examines contemporary social and economic challenges through rigorous empirical research and accessible analysis.
-
E.
American Made: What Happens to People When Work Disappears
American Made: What Happens to People When Work Disappears is a nonfiction book that examines the human and community consequences of deindustrialization and job loss in the United States through the stories of displaced factory workers.
- 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_69ca836320e48190b5cf585b90a322c4 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fb8aab88190befed16301e08efc |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6f6fdd688190bf40bbde0be991e1 |
completed | April 3, 2026, 7:42 a.m. |
| NEDg | Description generation | batch_69cf718a6f2c81908f8b8d08a1437749 |
completed | April 3, 2026, 7:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf7275fea08190b8999fb30663ff17 |
completed | April 3, 2026, 7:55 a.m. |
Created at: March 30, 2026, 6:44 p.m.