Triple

T18528219
Position Surface form Disambiguated ID Type / Status
Subject XHP E452771 entity
Predicate integratesWith P1075 FINISHED
Object Hack typechecker — 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: Hack typechecker | Statement: [XHP, integratesWith, Hack typechecker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hack typechecker
Context triple: [XHP, integratesWith, Hack typechecker]
  • A. PEP 647 TypeGuard
    PEP 647 TypeGuard is a Python typing feature that allows developers to define user-defined type guard functions, enabling more precise type narrowing and improved static type checking.
  • B. typer
    Typer is a modern, user-friendly Python library for building command-line interfaces, created by Sebastián Ramírez (tiangolo), the author of FastAPI.
  • C. HM type system
    The HM type system is a classical polymorphic type system used in many functional programming languages, known for its ability to infer the most general types without requiring explicit type annotations.
  • D. Static Code Checker
    Static Code Checker is a software tool that automatically analyzes source code without executing it to detect bugs, security vulnerabilities, and style or quality issues.
  • E. 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.
  • 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: Hack typechecker
Target entity description: The Hack typechecker is a static analysis tool for the Hack programming language that enforces strict typing and catches type-related errors before runtime.
  • A. PEP 647 TypeGuard
    PEP 647 TypeGuard is a Python typing feature that allows developers to define user-defined type guard functions, enabling more precise type narrowing and improved static type checking.
  • B. typer
    Typer is a modern, user-friendly Python library for building command-line interfaces, created by Sebastián Ramírez (tiangolo), the author of FastAPI.
  • C. HM type system
    The HM type system is a classical polymorphic type system used in many functional programming languages, known for its ability to infer the most general types without requiring explicit type annotations.
  • D. Static Code Checker
    Static Code Checker is a software tool that automatically analyzes source code without executing it to detect bugs, security vulnerabilities, and style or quality issues.
  • E. 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.
  • 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_69d8d387b5548190aa030dad2cb4947e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e533fad2d081908395914d6a6b4eb1 completed April 19, 2026, 7:58 p.m.
Created at: April 10, 2026, 11:37 a.m.