Triple

T4277862
Position Surface form Disambiguated ID Type / Status
Subject RStudio E97084 entity
Predicate supportsLanguage P2177 FINISHED
Object Markdown E182418 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: Markdown | Statement: [RStudio, supportsLanguage, Markdown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Markdown
Context triple: [RStudio, supportsLanguage, Markdown]
  • A. Markdown chosen
    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.
  • B. .md
    .md is the country code top-level domain (ccTLD) assigned to Moldova, also popularly used by medical professionals and sites related to medicine due to the "MD" abbreviation.
  • 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. reStructuredText
    reStructuredText is a lightweight, plaintext markup language commonly used in the Python ecosystem for documentation, including PEPs and Sphinx-based docs.
  • E. Rich Text Format
    Rich Text Format (RTF) is a cross-platform document file format developed by Microsoft that preserves basic text formatting and structure while remaining readable by many word processors.
  • 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_69b34544be3c819084d1ab82d29f90c5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3501ef1388190b0c968b069014a59 completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7b3b52c8190ae7c05448faf5558 completed March 14, 2026, 7:32 p.m.
Created at: March 12, 2026, 11:07 p.m.