Triple

T5892153
Position Surface form Disambiguated ID Type / Status
Subject The Complexity of Cooperation E131014 entity
Predicate contributesTo P477 FINISHED
Object foundations of algorithmic game theory
The foundations of algorithmic game theory comprise the core concepts and results at the intersection of game theory and theoretical computer science, focusing on computational aspects of strategic behavior, equilibria, and mechanism design.
E552831 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: foundations of algorithmic game theory | Statement: [The Complexity of Cooperation, contributesTo, foundations of algorithmic game theory]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: foundations of algorithmic game theory
Context triple: [The Complexity of Cooperation, contributesTo, foundations of algorithmic game theory]
  • A. Track A: Algorithms, Complexity and Games
    Track A: Algorithms, Complexity and Games is a main research track of the International Colloquium on Automata, Languages and Programming (ICALP) focusing on theoretical computer science topics such as algorithm design, computational complexity, and algorithmic game theory.
  • B. Game Theory (with Drew Fudenberg)
    "Game Theory (with Drew Fudenberg)" is a widely used graduate-level textbook that provides a rigorous and comprehensive introduction to modern game theory and its applications in economics.
  • C. game theory
    Game theory is a branch of mathematics and economics that studies strategic interactions among rational decision-makers, analyzing how individuals or groups choose actions when outcomes depend on the choices of others.
  • D. Dynamic Noncooperative Game Theory
    Dynamic Noncooperative Game Theory is a foundational book in game theory that rigorously analyzes strategic interactions among rational decision-makers evolving over time, with applications in economics, engineering, and control systems.
  • E. Non-cooperative Games
    Non-cooperative Games is John Nash’s seminal 1950 paper that founded modern non-cooperative game theory and introduced the concept now known as Nash equilibrium.
  • 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: foundations of algorithmic game theory
Triple: [The Complexity of Cooperation, contributesTo, foundations of algorithmic game theory]
Generated description
The foundations of algorithmic game theory comprise the core concepts and results at the intersection of game theory and theoretical computer science, focusing on computational aspects of strategic behavior, equilibria, and mechanism design.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: foundations of algorithmic game theory
Target entity description: The foundations of algorithmic game theory comprise the core concepts and results at the intersection of game theory and theoretical computer science, focusing on computational aspects of strategic behavior, equilibria, and mechanism design.
  • A. Track A: Algorithms, Complexity and Games
    Track A: Algorithms, Complexity and Games is a main research track of the International Colloquium on Automata, Languages and Programming (ICALP) focusing on theoretical computer science topics such as algorithm design, computational complexity, and algorithmic game theory.
  • B. Game Theory (with Drew Fudenberg)
    "Game Theory (with Drew Fudenberg)" is a widely used graduate-level textbook that provides a rigorous and comprehensive introduction to modern game theory and its applications in economics.
  • C. game theory
    Game theory is a branch of mathematics and economics that studies strategic interactions among rational decision-makers, analyzing how individuals or groups choose actions when outcomes depend on the choices of others.
  • D. Dynamic Noncooperative Game Theory
    Dynamic Noncooperative Game Theory is a foundational book in game theory that rigorously analyzes strategic interactions among rational decision-makers evolving over time, with applications in economics, engineering, and control systems.
  • E. Non-cooperative Games
    Non-cooperative Games is John Nash’s seminal 1950 paper that founded modern non-cooperative game theory and introduced the concept now known as Nash equilibrium.
  • 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_69c00857439c819095950754176aa58a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c036b45bec81908a13f39bbc181a59 completed March 22, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b14c2ff081908243988d5815be6d completed March 23, 2026, 3:19 a.m.
NEDg Description generation batch_69c0b1fabe448190be7d93b1f8c17c2a completed March 23, 2026, 3:22 a.m.
NED2 Entity disambiguation (via description) batch_69c0b29fbec8819092b117bd40e3731f completed March 23, 2026, 3:25 a.m.
Created at: March 22, 2026, 3:58 p.m.