Triple

T1255176
Position Surface form Disambiguated ID Type / Status
Subject lambda calculus E26971 entity
Predicate influenced P9 FINISHED
Object F# E34603 NE FINISHED

How this triple was built (2 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: F# | Statement: [lambda calculus, influenced, F#]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: F#
Context triple: [lambda calculus, influenced, F#]
  • A. F# chosen
    F# is a functional-first, multi-paradigm programming language for the .NET platform, known for its strong type system and concise, expressive syntax.
  • B. OCaml
    OCaml is a statically typed functional programming language from the ML family, known for its powerful type system, pattern matching, and efficient native code compilation.
  • C. ReasonML
    ReasonML is a syntax and toolchain for the OCaml language that offers a JavaScript-friendly, type-safe alternative for building web and native applications.
  • D. Haskell
    Haskell is a statically typed, purely functional programming language known for its strong type system, lazy evaluation, and use in both academic research and industry.
  • E. Scala
    Scala is a high-level, statically typed programming language that unifies object-oriented and functional programming paradigms and runs on the Java Virtual Machine.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a49487a9c48190ba9b05348fd1b53f completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bfa5a4cc819093ed686619b572d8 completed March 1, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac93cb76248190a23acb2e76ecfa8d completed March 7, 2026, 9:08 p.m.
Created at: March 1, 2026, 7:47 p.m.