Triple

T14721014
Position Surface form Disambiguated ID Type / Status
Subject Valiant–Vazirani theorem E345812 entity
Predicate showsHardnessOf P115516 FINISHED
Object Unique-SAT
Unique-SAT is a specialized version of the Boolean satisfiability problem where instances are guaranteed to have at most one satisfying assignment, and it plays a central role in complexity theory due to its connections to randomness and NP-completeness.
E1115574 NE FINISHED

How this triple was built (5 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: Unique-SAT | Statement: [Valiant–Vazirani theorem, showsHardnessOf, Unique-SAT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Unique-SAT
Context triple: [Valiant–Vazirani theorem, showsHardnessOf, Unique-SAT]
  • 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. 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.
  • 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. “Inapproximability results for SAT and other problems”
    “Inapproximability results for SAT and other problems” is a seminal theoretical computer science paper by Johan Håstad that establishes tight hardness-of-approximation bounds for satisfiability and related optimization problems using probabilistically checkable proofs.
  • E. TNTSAT
    TNTSAT is a French free-to-air satellite television platform that broadcasts the national digital terrestrial TV channels via satellite.
  • 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: Unique-SAT
Triple: [Valiant–Vazirani theorem, showsHardnessOf, Unique-SAT]
Generated description
Unique-SAT is a specialized version of the Boolean satisfiability problem where instances are guaranteed to have at most one satisfying assignment, and it plays a central role in complexity theory due to its connections to randomness and NP-completeness.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Unique-SAT
Target entity description: Unique-SAT is a specialized version of the Boolean satisfiability problem where instances are guaranteed to have at most one satisfying assignment, and it plays a central role in complexity theory due to its connections to randomness and NP-completeness.
  • 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. 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.
  • 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. “Inapproximability results for SAT and other problems”
    “Inapproximability results for SAT and other problems” is a seminal theoretical computer science paper by Johan Håstad that establishes tight hardness-of-approximation bounds for satisfiability and related optimization problems using probabilistically checkable proofs.
  • E. TNTSAT
    TNTSAT is a French free-to-air satellite television platform that broadcasts the national digital terrestrial TV channels via satellite.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: showsHardnessOf
Context triple: [Valiant–Vazirani theorem, showsHardnessOf, Unique-SAT]
  • A. hardness
    Indicates the degree to which one entity resists being scratched, indented, or deformed by another.
  • B. hardnessMohs
    Indicates the relative hardness of a material as measured on the Mohs scale of mineral hardness.
  • C. stoneQuality
    Indicates the quality or grade assigned to a stone in terms of its characteristics or condition.
  • D. hardiness
    Indicates the degree to which an entity can withstand or endure harsh, adverse, or challenging conditions.
  • E. hasMineral
    Indicates that one entity contains, includes, or is composed of a specified mineral.
  • F. None of above. chosen

Provenance (7 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec25d56fc8190871873ca55d49272 completed April 14, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf0957bb081908f1f382f3be8ec20 completed May 8, 2026, 2:17 p.m.
NEDg Description generation batch_69fdf440a03c8190886119ab3c8ab610 completed May 8, 2026, 2:33 p.m.
NED2 Entity disambiguation (via description) batch_69fdf4f2acbc8190b51ee456093a2813 completed May 8, 2026, 2:36 p.m.
PD Predicate disambiguation batch_69de657e174481909da0437556334a04 completed April 14, 2026, 4:04 p.m.
PDg Predicate description generation batch_69de716d3aac8190aaa6dc1f099b86e8 completed April 14, 2026, 4:55 p.m.
Created at: April 10, 2026, 1:29 a.m.