Triple

T4277896
Position Surface form Disambiguated ID Type / Status
Subject RStudio E97084 entity
Predicate supportsDocumentFormat P20985 FINISHED
Object R Markdown E426693 NE FINISHED

How this triple was built (3 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: R Markdown | Statement: [RStudio, supportsDocumentFormat, R Markdown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: R Markdown
Context triple: [RStudio, supportsDocumentFormat, R Markdown]
  • A. R Markdown chosen
    R Markdown is a file format and authoring framework that combines R code with narrative text to create dynamic, reproducible documents, reports, and presentations.
  • B. 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.
  • C. LaTeX
    LaTeX is a widely used, high-quality typesetting system particularly popular in academia for producing technical and scientific documents with precise control over layout and mathematical notation.
  • D. LyX
    LyX is an open-source, document processor and graphical front-end for LaTeX that lets users create structured, professional-quality documents without directly writing LaTeX code.
  • E. reStructuredText
    reStructuredText is a lightweight, plaintext markup language commonly used in the Python ecosystem for documentation, including PEPs and Sphinx-based docs.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: supportsDocumentFormat
Context triple: [RStudio, supportsDocumentFormat, R Markdown]
  • A. supportsDocument chosen
    Indicates that one entity provides compatibility or functionality for handling, processing, or using a particular document or document type.
  • B. hasFileFormat
    Indicates that one entity (typically a digital file or resource) is encoded, stored, or represented using a specific file format defined by the other entity.
  • C. operatesInFormat
    Indicates that an entity functions, performs its role, or is carried out using a specified format.
  • D. recognizesDocument
    Indicates that one entity acknowledges the validity or authenticity of a document associated with another entity.
  • E. supportsOffice
    Indicates that one entity provides assistance, resources, or endorsement to an office or officeholder in performing its functions or maintaining its operations.
  • F. None of above.

Provenance (4 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_69b5c7237b608190ab5aca56027344c4 completed March 14, 2026, 8:37 p.m.
PD Predicate disambiguation batch_69b347faa45481908c19c29fb906dc92 completed March 12, 2026, 11:10 p.m.
Created at: March 12, 2026, 11:07 p.m.