Triple

T4442696
Position Surface form Disambiguated ID Type / Status
Subject Hanami E96208 entity
Predicate supportsTemplateEngines P203 FINISHED
Object Haml E436322 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: Haml | Statement: [Hanami, supportsTemplateEngines, Haml]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haml
Context triple: [Hanami, supportsTemplateEngines, Haml]
  • A. Haml chosen
    Haml is a whitespace-sensitive templating language for Ruby that provides a clean, indentation-based syntax for generating HTML.
  • B. Handlebars
    Handlebars is a popular logic-less templating engine for JavaScript that enables clean, readable templates with embedded expressions for dynamic HTML generation.
  • C. Jekyll
    Jekyll is a 2007 British television drama series created by Steven Moffat that offers a modern, suspenseful reimagining of Robert Louis Stevenson’s classic Dr. Jekyll and Mr. Hyde story.
  • D. CoffeeScript
    CoffeeScript is a programming language that compiles to JavaScript, offering a more concise, Python- and Ruby-like syntax for writing web application code.
  • E. Jekyll static site generator
    Jekyll is a popular open-source static site generator, written in Ruby, that transforms plain text files into simple, blog-aware websites without requiring a database.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3564216b081908c41109100b36862 completed March 13, 2026, 12:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69b61382d00481908b7c84f337b5cad7 completed March 15, 2026, 2:03 a.m.
Created at: March 12, 2026, 11:32 p.m.