Triple

T1159989
Position Surface form Disambiguated ID Type / Status
Subject ECMAScript E24470 entity
Predicate influences P9 FINISHED
Object Dart (early versions) E24475 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: Dart (early versions) | Statement: [ECMAScript, influences, Dart (early versions)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dart (early versions)
Context triple: [ECMAScript, influences, Dart (early versions)]
  • A. Dart chosen
    Dart is a client-optimized, object-oriented programming language developed by Google, primarily used for building web and cross-platform mobile applications (notably with the Flutter framework).
  • B. V8
    V8 is Google’s high-performance open-source JavaScript engine, used in Chrome and Node.js to compile and execute JavaScript directly to native machine code.
  • C. V8
    V8 is a popular vegetable-based juice brand known for its blended vegetable and fruit beverages marketed as a nutritious drink option.
  • D. Deno
    Deno is a modern, secure JavaScript and TypeScript runtime created by Ryan Dahl as a successor to Node.js, featuring built-in TypeScript support and a permission-based security model.
  • E. Elm
    Elm is a civil parish and village in Cambridgeshire, England, known for its rural character and historic church.
  • 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.