Triple

T18256794
Position Surface form Disambiguated ID Type / Status
Subject MoonScript E437238 entity
Predicate influencedBy P9 FINISHED
Object CoffeeScript NE NERFINISHED

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: CoffeeScript | Statement: [MoonScript, influencedBy, CoffeeScript]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CoffeeScript
Context triple: [MoonScript, influencedBy, CoffeeScript]
  • A. CoffeeScript chosen
    CoffeeScript is a programming language that compiles to JavaScript, offering a more concise, Python- and Ruby-like syntax for writing web application code.
  • B. Moonscript
    Moonscript is a high-level programming language that compiles to Lua, offering a cleaner, more expressive syntax while targeting the Lua runtime.
  • C. PureScript
    PureScript is a strongly-typed, purely functional programming language that compiles to JavaScript and is heavily inspired by Haskell.
  • D. Haml
    Haml is a whitespace-sensitive templating language for Ruby that provides a clean, indentation-based syntax for generating HTML.
  • E. Elixir
    Elixir is a functional, concurrent programming language built on the Erlang VM, known for its scalability, fault tolerance, and expressive syntax.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69e4fd86e21081909c049082949b95c6 completed April 19, 2026, 4:06 p.m.
Created at: April 10, 2026, 10:34 a.m.