Triple
T5382655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billy Beane |
E113124
|
entity |
| Predicate | subjectOf |
P38
|
FINISHED |
| Object |
book "Moneyball: The Art of Winning an Unfair Game"
"Moneyball: The Art of Winning an Unfair Game" is a non-fiction book by Michael Lewis that chronicles how the Oakland Athletics used data-driven, sabermetric analysis to build a competitive baseball team on a limited budget.
|
E516452
|
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: book "Moneyball: The Art of Winning an Unfair Game" | Statement: [Billy Beane, subjectOf, book "Moneyball: The Art of Winning an Unfair Game"]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: book "Moneyball: The Art of Winning an Unfair Game" Context triple: [Billy Beane, subjectOf, book "Moneyball: The Art of Winning an Unfair Game"]
-
A.
Moneyball
Moneyball is a 2011 sports drama film (based on Michael Lewis’s nonfiction book) that chronicles the Oakland Athletics’ pioneering use of sabermetrics and data-driven analysis to build a competitive baseball team on a limited budget.
-
B.
book "Fourth and One"
"Fourth and One" is a book by legendary NFL coach Joe Gibbs that reflects on his football career, leadership philosophy, and life lessons learned on and off the field.
-
C.
book "Go Up for Glory"
"Go Up for Glory" is an autobiography in which legendary NBA center Bill Russell reflects on his life, basketball career, and experiences with race and social justice in America.
-
D.
For the Good of the Game: The Inside Story of the Surprising and Dramatic Transformation of Major League Baseball
"For the Good of the Game: The Inside Story of the Surprising and Dramatic Transformation of Major League Baseball" is a memoir by former MLB commissioner Bud Selig that chronicles the league’s modern evolution, controversies, and reforms from his insider perspective.
-
E.
book "Flash Boys" by Michael Lewis
"Flash Boys" is a non-fiction book by Michael Lewis that investigates the rise of high-frequency trading on Wall Street and the efforts of a group of traders to expose and reform what they saw as a rigged financial system.
- 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: book "Moneyball: The Art of Winning an Unfair Game" Triple: [Billy Beane, subjectOf, book "Moneyball: The Art of Winning an Unfair Game"]
Generated description
"Moneyball: The Art of Winning an Unfair Game" is a non-fiction book by Michael Lewis that chronicles how the Oakland Athletics used data-driven, sabermetric analysis to build a competitive baseball team on a limited budget.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: book "Moneyball: The Art of Winning an Unfair Game" Target entity description: "Moneyball: The Art of Winning an Unfair Game" is a non-fiction book by Michael Lewis that chronicles how the Oakland Athletics used data-driven, sabermetric analysis to build a competitive baseball team on a limited budget.
-
A.
Moneyball
Moneyball is a 2011 sports drama film (based on Michael Lewis’s nonfiction book) that chronicles the Oakland Athletics’ pioneering use of sabermetrics and data-driven analysis to build a competitive baseball team on a limited budget.
-
B.
book "Fourth and One"
"Fourth and One" is a book by legendary NFL coach Joe Gibbs that reflects on his football career, leadership philosophy, and life lessons learned on and off the field.
-
C.
book "Go Up for Glory"
"Go Up for Glory" is an autobiography in which legendary NBA center Bill Russell reflects on his life, basketball career, and experiences with race and social justice in America.
-
D.
For the Good of the Game: The Inside Story of the Surprising and Dramatic Transformation of Major League Baseball
"For the Good of the Game: The Inside Story of the Surprising and Dramatic Transformation of Major League Baseball" is a memoir by former MLB commissioner Bud Selig that chronicles the league’s modern evolution, controversies, and reforms from his insider perspective.
-
E.
book "Flash Boys" by Michael Lewis
"Flash Boys" is a non-fiction book by Michael Lewis that investigates the rise of high-frequency trading on Wall Street and the efforts of a group of traders to expose and reform what they saw as a rigged financial system.
- 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_69bd4436a1988190af18dcff7fd306b4 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd86d163f88190939638d44fcb24a7 |
completed | March 20, 2026, 5:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf294cb9288190ab1400dae18332de |
completed | March 21, 2026, 11:27 p.m. |
| NEDg | Description generation | batch_69bf2a23ba1881909ddc549728bbc2d3 |
completed | March 21, 2026, 11:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf2e6d5f9081908327dff0058241f0 |
completed | March 21, 2026, 11:49 p.m. |
Created at: March 20, 2026, 2:03 p.m.