Triple

T1160342
Position Surface form Disambiguated ID Type / Status
Subject Elm E24476 entity
Predicate influencedBy P9 FINISHED
Object Haskell E95186 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: Haskell | Statement: [Elm, influencedBy, Haskell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haskell
Context triple: [Elm, influencedBy, Haskell]
  • A. Haskell chosen
    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.
  • B. 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.
  • C. F#
    F# is a functional-first, multi-paradigm programming language for the .NET platform, known for its strong type system and concise, expressive syntax.
  • D. Elm
    Elm is a civil parish and village in Cambridgeshire, England, known for its rural character and historic church.
  • E. Elm
    Elm is a statically typed, functional programming language that compiles to JavaScript and is designed for building reliable, maintainable web front-end applications.
  • 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_69a494060e148190abb42f971242c197 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bcaf3a9081908bad2eba74dffbc1 completed March 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac5ebbf80881909010e1e1e59212d4 completed March 7, 2026, 5:22 p.m.
Created at: March 1, 2026, 7:45 p.m.