Triple

T11090191
Position Surface form Disambiguated ID Type / Status
Subject Satisfiability Modulo Theories E262229 entity
Predicate hasSolver P55156 FINISHED
Object MathSAT
MathSAT is a widely used SMT (Satisfiability Modulo Theories) solver designed to efficiently decide the satisfiability of logical formulas over combinations of theories such as arithmetic, bit-vectors, and arrays.
E262229 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: MathSAT | Statement: [Satisfiability Modulo Theories, hasSolver, MathSAT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MathSAT
Context triple: [Satisfiability Modulo Theories, hasSolver, MathSAT]
  • A. CDCL SAT solver
    A CDCL SAT solver is an advanced algorithm for solving Boolean satisfiability problems that extends the classic DPLL approach with conflict-driven clause learning and non-chronological backtracking to greatly improve efficiency on large, complex instances.
  • B. Satisfiability Modulo Theories (SMT)
    Satisfiability Modulo Theories (SMT) is a framework in computer science and mathematical logic for deciding the satisfiability of logical formulas with respect to background theories such as arithmetic, bit-vectors, arrays, and data types, widely used in verification, synthesis, and automated reasoning.
  • C. Max-SAT
    Max-SAT is the optimization variant of the Boolean satisfiability problem in which the goal is to find an assignment that satisfies the maximum possible number of clauses, making it a central problem in approximation algorithms and complexity theory.
  • D. TNTSAT
    TNTSAT is a French free-to-air satellite television platform that broadcasts the national digital terrestrial TV channels via satellite.
  • E. Z3 SMT solver
    Z3 SMT solver is a high-performance Satisfiability Modulo Theories (SMT) solver developed at Microsoft Research, widely used in program verification, formal methods, and automated reasoning.
  • 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: MathSAT
Triple: [Satisfiability Modulo Theories, hasSolver, MathSAT]
Generated description
MathSAT is a widely used SMT (Satisfiability Modulo Theories) solver designed to efficiently decide the satisfiability of logical formulas over combinations of theories such as arithmetic, bit-vectors, and arrays.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MathSAT
Target entity description: MathSAT is a widely used SMT (Satisfiability Modulo Theories) solver designed to efficiently decide the satisfiability of logical formulas over combinations of theories such as arithmetic, bit-vectors, and arrays.
  • A. CDCL SAT solver
    A CDCL SAT solver is an advanced algorithm for solving Boolean satisfiability problems that extends the classic DPLL approach with conflict-driven clause learning and non-chronological backtracking to greatly improve efficiency on large, complex instances.
  • B. Satisfiability Modulo Theories (SMT) chosen
    Satisfiability Modulo Theories (SMT) is a framework in computer science and mathematical logic for deciding the satisfiability of logical formulas with respect to background theories such as arithmetic, bit-vectors, arrays, and data types, widely used in verification, synthesis, and automated reasoning.
  • C. Max-SAT
    Max-SAT is the optimization variant of the Boolean satisfiability problem in which the goal is to find an assignment that satisfies the maximum possible number of clauses, making it a central problem in approximation algorithms and complexity theory.
  • D. TNTSAT
    TNTSAT is a French free-to-air satellite television platform that broadcasts the national digital terrestrial TV channels via satellite.
  • E. Z3 SMT solver
    Z3 SMT solver is a high-performance Satisfiability Modulo Theories (SMT) solver developed at Microsoft Research, widely used in program verification, formal methods, and automated reasoning.
  • F. None of above.

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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799e96ca08190838c8a04d1eb2a16 completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7c586808190a576803b7406a49e completed April 18, 2026, 8:21 p.m.
NEDg Description generation batch_69e3f2cafc008190a3504999297f1e4e completed April 18, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_69e3f488819081908f9a4225279cde6b completed April 18, 2026, 9:15 p.m.
Created at: April 8, 2026, 9:27 p.m.