Triple

T1611095
Position Surface form Disambiguated ID Type / Status
Subject Tom Preston-Werner E34614 entity
Predicate created P538 FINISHED
Object Jekyll E183285 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: Jekyll | Statement: [Tom Preston-Werner, created, Jekyll]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jekyll
Context triple: [Tom Preston-Werner, created, Jekyll]
  • A. Jekyll static site generator chosen
    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.
  • B. Rubinius
    Rubinius is an alternative Ruby implementation featuring a virtual machine and just-in-time compilation, designed for high performance and concurrency.
  • C. Markdown
    Markdown is a lightweight markup language that uses plain-text formatting syntax to create structured documents, most commonly used for README files, documentation, and web content.
  • D. GitHub Pages
    GitHub Pages is a static site hosting service that lets users publish web pages directly from their GitHub repositories.
  • E. The Rack
    The Rack is a 1956 courtroom drama film about the psychological and moral aftermath of a Korean War veteran’s imprisonment and alleged collaboration with the enemy.
  • 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_69a885ffc5ec819091afa325d5f9611c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa622b9fbc8190bff82acdde10deb6 completed March 6, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad58c6d7e88190b9fc0e34a007a2f5 completed March 8, 2026, 11:08 a.m.
Created at: March 4, 2026, 7:28 p.m.