Triple

T18256074
Position Surface form Disambiguated ID Type / Status
Subject GHC E437224 entity
Predicate supportsExtension P203 FINISHED
Object Multi-parameter Type Classes — 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: Multi-parameter Type Classes | Statement: [GHC, supportsExtension, Multi-parameter Type Classes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Multi-parameter Type Classes
Context triple: [GHC, supportsExtension, Multi-parameter Type Classes]
  • A. Hindley–Milner type system
    The Hindley–Milner type system is a classical polymorphic type system used in many functional programming languages, notable for enabling type inference without explicit type annotations.
  • B. "Advanced Topics in Types and Programming Languages"
    "Advanced Topics in Types and Programming Languages" is a graduate-level computer science book that explores advanced concepts in type systems and their applications to programming language design and semantics.
  • C. "Types and Programming Languages"
    "Types and Programming Languages" is a widely acclaimed textbook that provides a rigorous, foundational introduction to type systems and programming language theory for computer science students and researchers.
  • D. “Linear Types Can Change the World!”
    “Linear Types Can Change the World!” is a seminal research paper in programming languages that advocates for the use of linear type systems to improve resource management, safety, and efficiency in software.
  • E. Structural Pattern Matching
    Structural Pattern Matching is a Python language feature, introduced via PEP 622, that enables powerful, declarative matching of complex data structures using a `match`/`case` syntax.
  • 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: Multi-parameter Type Classes
Target entity description: Multi-parameter Type Classes are a Haskell language feature that allows type classes to take multiple type parameters, enabling more expressive relationships between types than single-parameter type classes.
  • A. Hindley–Milner type system
    The Hindley–Milner type system is a classical polymorphic type system used in many functional programming languages, notable for enabling type inference without explicit type annotations.
  • B. "Advanced Topics in Types and Programming Languages"
    "Advanced Topics in Types and Programming Languages" is a graduate-level computer science book that explores advanced concepts in type systems and their applications to programming language design and semantics.
  • C. "Types and Programming Languages"
    "Types and Programming Languages" is a widely acclaimed textbook that provides a rigorous, foundational introduction to type systems and programming language theory for computer science students and researchers.
  • D. “Linear Types Can Change the World!”
    “Linear Types Can Change the World!” is a seminal research paper in programming languages that advocates for the use of linear type systems to improve resource management, safety, and efficiency in software.
  • E. Structural Pattern Matching
    Structural Pattern Matching is a Python language feature, introduced via PEP 622, that enables powerful, declarative matching of complex data structures using a `match`/`case` syntax.
  • 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_69d8b913351c8190932b6a426de04b41 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4fd85ee548190a102611fcf709ad4 completed April 19, 2026, 4:06 p.m.
Created at: April 10, 2026, 10:34 a.m.