Triple

T1160013
Position Surface form Disambiguated ID Type / Status
Subject ECMAScript E24470 entity
Predicate editionAlias P39 FINISHED
Object ECMAScript 2016 = ES7 E24470 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: ECMAScript 2016 = ES7 | Statement: [ECMAScript, editionAlias, ECMAScript 2016 = ES7]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ECMAScript 2016 = ES7
Context triple: [ECMAScript, editionAlias, ECMAScript 2016 = ES7]
  • A. ECMAScript chosen
    ECMAScript is the official scripting language specification that defines the core features and behavior implemented by JavaScript and related languages.
  • B. TC39
    TC39 is the Ecma International committee responsible for developing and standardizing the ECMAScript language, which underpins JavaScript.
  • C. 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.
  • D. V8
    V8 is a popular vegetable-based juice brand known for its blended vegetable and fruit beverages marketed as a nutritious drink option.
  • E. 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.
  • 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_69a4bf13ab648190931dea78202096e4 completed March 1, 2026, 10:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7642ff0c81909b323ac328b18e2e completed March 7, 2026, 7:02 p.m.
Created at: March 1, 2026, 7:45 p.m.