Triple

T17228997
Position Surface form Disambiguated ID Type / Status
Subject John Harsanyi E418194 entity
Predicate knownFor P22 FINISHED
Object Harsanyi transformation
The Harsanyi transformation is a game-theoretic method that converts games with incomplete information into games with imperfect information by introducing "types" and a common prior over them.
E1257391 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: Harsanyi transformation | Statement: [John Harsanyi, knownFor, Harsanyi transformation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harsanyi transformation
Context triple: [John Harsanyi, knownFor, Harsanyi transformation]
  • A. Kuhn’s theorem
    Kuhn’s theorem is a fundamental result in game theory that shows any finite extensive-form game with perfect recall has an equivalent normal-form (strategic-form) representation, ensuring the existence of mixed-strategy equilibria.
  • B. “Extensive Games and the Problem of Information”
    “Extensive Games and the Problem of Information” is a foundational paper in game theory by Harold W. Kuhn that formalizes extensive-form games and introduces key concepts for analyzing strategic interaction under imperfect information.
  • C. expected utility theory (with John von Neumann)
    Expected utility theory (with John von Neumann) is a foundational framework in economics and decision theory that models how rational agents make choices under uncertainty by maximizing the expected value of a utility function.
  • D. Nash equilibrium
    A Nash equilibrium is a game-theoretic solution concept where no player can improve their payoff by unilaterally changing their strategy, given the strategies of all other players.
  • E. Kalai–Smorodinsky bargaining solution
    The Kalai–Smorodinsky bargaining solution is a cooperative game theory concept that selects a fair agreement between parties by preserving proportional gains relative to their best possible outcomes.
  • 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: Harsanyi transformation
Triple: [John Harsanyi, knownFor, Harsanyi transformation]
Generated description
The Harsanyi transformation is a game-theoretic method that converts games with incomplete information into games with imperfect information by introducing "types" and a common prior over them.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Harsanyi transformation
Target entity description: The Harsanyi transformation is a game-theoretic method that converts games with incomplete information into games with imperfect information by introducing "types" and a common prior over them.
  • A. Kuhn’s theorem
    Kuhn’s theorem is a fundamental result in game theory that shows any finite extensive-form game with perfect recall has an equivalent normal-form (strategic-form) representation, ensuring the existence of mixed-strategy equilibria.
  • B. “Extensive Games and the Problem of Information”
    “Extensive Games and the Problem of Information” is a foundational paper in game theory by Harold W. Kuhn that formalizes extensive-form games and introduces key concepts for analyzing strategic interaction under imperfect information.
  • C. expected utility theory (with John von Neumann)
    Expected utility theory (with John von Neumann) is a foundational framework in economics and decision theory that models how rational agents make choices under uncertainty by maximizing the expected value of a utility function.
  • D. Nash equilibrium
    A Nash equilibrium is a game-theoretic solution concept where no player can improve their payoff by unilaterally changing their strategy, given the strategies of all other players.
  • E. Kalai–Smorodinsky bargaining solution
    The Kalai–Smorodinsky bargaining solution is a cooperative game theory concept that selects a fair agreement between parties by preserving proportional gains relative to their best possible outcomes.
  • 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_69d886d8e96081909870bff6c3d0bf09 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42df55e788190b442ffd4fac768c9 completed April 19, 2026, 1:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01675eae08819093427b4dc1ffee5f completed May 11, 2026, 5:21 a.m.
NEDg Description generation batch_6a016a1f6eac8190951ae30f37144d2a completed May 11, 2026, 5:33 a.m.
NED2 Entity disambiguation (via description) batch_6a016a92af248190aaed36040486bf40 completed May 11, 2026, 5:35 a.m.
Created at: April 10, 2026, 5:39 a.m.