Triple

T9838515
Position Surface form Disambiguated ID Type / Status
Subject Symbolic Model Checking E239161 entity
Predicate usesDataStructure P32204 FINISHED
Object OBDDs
OBDDs (Ordered Binary Decision Diagrams) are a canonical, graph-based representation of Boolean functions that enables efficient manipulation and verification in formal methods and model checking.
E824078 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: OBDDs | Statement: [Symbolic Model Checking, usesDataStructure, OBDDs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OBDDs
Context triple: [Symbolic Model Checking, usesDataStructure, OBDDs]
  • A. Davis–Putnam algorithm
    The Davis–Putnam algorithm is a pioneering procedure in automated theorem proving and propositional logic satisfiability that laid foundational groundwork for modern SAT solvers.
  • 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. 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.
  • D. OBDA systems
    OBDA systems are software frameworks that enable querying heterogeneous data sources through an ontology-based abstraction layer, typically using languages like OWL 2 QL to provide semantic integration and efficient query answering.
  • E. Edge-Based Clausal Syntax
    Edge-Based Clausal Syntax is a theoretical linguistics work by Paul Postal that develops a clause structure framework organized around hierarchical edge positions rather than traditional phrase-structure configurations.
  • 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: OBDDs
Triple: [Symbolic Model Checking, usesDataStructure, OBDDs]
Generated description
OBDDs (Ordered Binary Decision Diagrams) are a canonical, graph-based representation of Boolean functions that enables efficient manipulation and verification in formal methods and model checking.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: OBDDs
Target entity description: OBDDs (Ordered Binary Decision Diagrams) are a canonical, graph-based representation of Boolean functions that enables efficient manipulation and verification in formal methods and model checking.
  • A. Davis–Putnam algorithm
    The Davis–Putnam algorithm is a pioneering procedure in automated theorem proving and propositional logic satisfiability that laid foundational groundwork for modern SAT solvers.
  • 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. 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.
  • D. OBDA systems
    OBDA systems are software frameworks that enable querying heterogeneous data sources through an ontology-based abstraction layer, typically using languages like OWL 2 QL to provide semantic integration and efficient query answering.
  • E. Edge-Based Clausal Syntax
    Edge-Based Clausal Syntax is a theoretical linguistics work by Paul Postal that develops a clause structure framework organized around hierarchical edge positions rather than traditional phrase-structure configurations.
  • 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb34921b881909836ba0f5b42a27b completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5d145ac8190ad10a4328216ef54 completed April 5, 2026, 3:24 a.m.
NEDg Description generation batch_69d1d6bb23cc81909efbeccf147018e8 completed April 5, 2026, 3:27 a.m.
NED2 Entity disambiguation (via description) batch_69d1d726e58c819090135d1ff275d2d8 completed April 5, 2026, 3:29 a.m.
Created at: March 30, 2026, 8:33 p.m.