Triple

T25930008
Position Surface form Disambiguated ID Type / Status
Subject Nim E653412 entity
Predicate hasSolutionDescribedIn P65108 FINISHED
Object Bouton’s theorem
Bouton’s theorem is a fundamental result in combinatorial game theory that characterizes winning and losing positions in the game of Nim using binary (xor) addition of heap sizes.
 E1702627 NE FINISHED

How this triple was built (3 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: Bouton’s theorem | Statement: [Nim, hasSolutionDescribedIn, Bouton’s theorem]
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: Bouton’s theorem
Triple: [Nim, hasSolutionDescribedIn, Bouton’s theorem]
Generated description
Bouton’s theorem is a fundamental result in combinatorial game theory that characterizes winning and losing positions in the game of Nim using binary (xor) addition of heap sizes.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasSolutionDescribedIn
Context triple: [Nim, hasSolutionDescribedIn, Bouton’s theorem]
  • A. providesSolutionFor chosen
    Indicates that one entity offers or supplies a remedy, answer, or resolution to a problem, need, or issue associated with another entity.
  • B. admitsSolution
    Indicates that a problem, system, or situation allows for or possesses at least one valid solution.
  • C. isSolutionOf
    Indicates that one entity is a correct answer or satisfies the conditions of a given problem, equation, or task.
  • D. hasSolutionSpace
    Indicates that there exists a set of possible solutions or outcomes associated with a given problem, constraint, or system.
  • E. requiresSolutionMethod
    Indicates that one entity necessitates a particular method or procedure to solve, address, or complete another entity or problem.
  • F. None of above.

Provenance (6 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_69e7ab3eb9b881909c1390690551f868 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f65aa07c048190a5df30d53d8f0cf5 completed May 2, 2026, 8:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecd7cbfc8190a8cd9dd70f2b80cf completed May 22, 2026, 11:55 p.m.
NEDg Description generation batch_6a10f01889d881908727fbc2726d10f2 completed May 23, 2026, 12:08 a.m.
NED2 Entity disambiguation (via description) batch_6a10f40d53ec8190abf974d50b4374e2 completed May 23, 2026, 12:25 a.m.
PD Predicate disambiguation batch_69f659cc571c819097e51e531961d812 completed May 2, 2026, 8:08 p.m.
Created at: April 22, 2026, 8:36 a.m.