Triple

T21088258
Position Surface form Disambiguated ID Type / Status
Subject Reducibility Among Combinatorial Problems E519559 entity
Predicate establishesNPCompletenessOf P142028 FINISHED
Object 3-Dimensional Matching problem NE NERFINISHED

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: 3-Dimensional Matching problem | Statement: [Reducibility Among Combinatorial Problems, establishesNPCompletenessOf, 3-Dimensional Matching problem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 3-Dimensional Matching problem
Context triple: [Reducibility Among Combinatorial Problems, establishesNPCompletenessOf, 3-Dimensional Matching problem]
  • A. 3-SAT
    3-SAT is a classic Boolean satisfiability problem where each clause has exactly three literals and which serves as a fundamental NP-complete benchmark in computational complexity theory.
  • B. Clique problem
    The Clique problem is a classic NP-complete decision problem in graph theory that asks whether a graph contains a fully connected subgraph (clique) of at least a given size.
  • C. Max-3-SAT
    Max-3-SAT is an optimization variant of the Boolean satisfiability problem where the goal is to maximize the number of satisfied clauses, each containing exactly three literals, and it serves as a central problem in the study of approximation algorithms and hardness of approximation.
  • D. A Combinatorial Problem
    "A Combinatorial Problem" is a classic mathematical paper by N. G. de Bruijn that introduces and analyzes a fundamental counting problem in combinatorics.
  • E. Happy Ending problem
    The Happy Ending problem is a famous combinatorial geometry question that investigates the minimum number of points in general position in the plane needed to guarantee the existence of a convex polygon with a given number of vertices.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 3-Dimensional Matching problem
Target entity description: The 3-Dimensional Matching problem is a classic NP-complete combinatorial decision problem that asks whether there exists a perfect matching selecting disjoint triples from three equally sized sets.
  • A. 3-SAT
    3-SAT is a classic Boolean satisfiability problem where each clause has exactly three literals and which serves as a fundamental NP-complete benchmark in computational complexity theory.
  • B. Clique problem
    The Clique problem is a classic NP-complete decision problem in graph theory that asks whether a graph contains a fully connected subgraph (clique) of at least a given size.
  • C. Max-3-SAT
    Max-3-SAT is an optimization variant of the Boolean satisfiability problem where the goal is to maximize the number of satisfied clauses, each containing exactly three literals, and it serves as a central problem in the study of approximation algorithms and hardness of approximation.
  • D. A Combinatorial Problem
    "A Combinatorial Problem" is a classic mathematical paper by N. G. de Bruijn that introduces and analyzes a fundamental counting problem in combinatorics.
  • E. Happy Ending problem
    The Happy Ending problem is a famous combinatorial geometry question that investigates the minimum number of points in general position in the plane needed to guarantee the existence of a convex polygon with a given number of vertices.
  • F. None of above. chosen

Provenance (2 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_69e0b507dd9081908fb8bfcbef4c8b46 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7094cebe08190bb10f51a45c244ec completed April 21, 2026, 5:21 a.m.
Created at: April 16, 2026, 2:50 p.m.