Triple

T25930006
Position Surface form Disambiguated ID Type / Status
Subject Nim E653412 entity
Predicate hasHistoricalAnalysisBy P62814 FINISHED
Object Charles L. Bouton
Charles L. Bouton was an American mathematician known for his pioneering work in combinatorial game theory, particularly his formal analysis of the impartial game Nim.
 E1702626 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: Charles L. Bouton | Statement: [Nim, hasHistoricalAnalysisBy, Charles L. Bouton]
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: Charles L. Bouton
Triple: [Nim, hasHistoricalAnalysisBy, Charles L. Bouton]
Generated description
Charles L. Bouton was an American mathematician known for his pioneering work in combinatorial game theory, particularly his formal analysis of the impartial game Nim.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasHistoricalAnalysisBy
Context triple: [Nim, hasHistoricalAnalysisBy, Charles L. Bouton]
  • A. usesHistoricalAnalysis
    Indicates that an entity employs historical analysis as a method or approach to understand, evaluate, or explain something.
  • B. hasHistoricalData
    Indicates that an entity possesses recorded information or records about past events, states, or values relevant to it.
  • C. hasHistoricalDetail
    Indicates that something includes or is associated with specific information about past events, contexts, or developments.
  • D. hasAnalysis chosen
    Indicates that an entity is associated with, or has undergone, a particular analysis or examination.
  • E. hasHistoryIn
    Indicates that an entity has a past involvement, presence, or record of activity within a particular domain, context, or location.
  • 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_69f6e6029a10819098ff21f58079e70e completed May 3, 2026, 6:06 a.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_69f6e3d5e8188190b1e1c2e5d1b77031 completed May 3, 2026, 5:57 a.m.
Created at: April 22, 2026, 8:36 a.m.