Triple

T18255757
Position Surface form Disambiguated ID Type / Status
Subject Practical Extraction and Report Language E437218 entity
Predicate influenced P9 FINISHED
Object JavaScript 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: JavaScript | Statement: [Practical Extraction and Report Language, influenced, JavaScript]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: JavaScript
Context triple: [Practical Extraction and Report Language, influenced, JavaScript]
  • A. JavaScript chosen
    JavaScript is a high-level, dynamic programming language primarily used to create interactive and dynamic content on web pages.
  • B. JS
    JS is the youth wing of the Dutch Labour Party (PvdA), organizing and representing young social democrats in the Netherlands.
  • C. JS
    JS is the commonly used abbreviation for the United States military’s Joint Staff, which assists the Chairman of the Joint Chiefs of Staff in strategic planning and coordination among the armed services.
  • D. JS
    JS is the IATA airline designator assigned to Air Koryo, the state-owned flag carrier of North Korea.
  • E. JScript
    JScript is Microsoft's dialect of the ECMAScript scripting language, primarily used for client-side scripting in Internet Explorer and for automation tasks in Windows environments.
  • 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_69e4fd85ee548190a102611fcf709ad4 completed April 19, 2026, 4:06 p.m.
Created at: April 10, 2026, 10:34 a.m.