Triple

T5340432
Position Surface form Disambiguated ID Type / Status
Subject EDGAR E123930 entity
Predicate dataFormat P130 FINISHED
Object XBRL
XBRL (eXtensible Business Reporting Language) is an XML-based global standard for tagging and exchanging business and financial data in a structured, machine-readable format.
 E512102 NE FINISHED

How this triple was built (4 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: XBRL | Statement: [EDGAR, dataFormat, XBRL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: XBRL
Context triple: [EDGAR, dataFormat, XBRL]
  • A. XML
    XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
  • B. LSXMB
    LSXMB is a series of Liberty Media Corporation’s tracking stock that reflects the economic performance of its SiriusXM Group.
  • C. XHTML
    XHTML is a reformulation of HTML as an XML-based markup language designed to create structured, standards-compliant web pages.
  • D. EDGAR
    EDGAR is the U.S. Securities and Exchange Commission’s electronic filing system that provides public access to corporate financial and disclosure documents.
  • E. XLink
    XLink is an XML standard that extends basic linking capabilities by enabling rich, multidirectional, and metadata-enhanced hyperlinks between resources.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: XBRL
Triple: [EDGAR, dataFormat, XBRL]
Generated description
XBRL (eXtensible Business Reporting Language) is an XML-based global standard for tagging and exchanging business and financial data in a structured, machine-readable format.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: XBRL
Target entity description: XBRL (eXtensible Business Reporting Language) is an XML-based global standard for tagging and exchanging business and financial data in a structured, machine-readable format.
  • A. XML
    XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
  • B. LSXMB
    LSXMB is a series of Liberty Media Corporation’s tracking stock that reflects the economic performance of its SiriusXM Group.
  • C. XHTML
    XHTML is a reformulation of HTML as an XML-based markup language designed to create structured, standards-compliant web pages.
  • D. EDGAR
    EDGAR is the U.S. Securities and Exchange Commission’s electronic filing system that provides public access to corporate financial and disclosure documents.
  • E. XLink
    XLink is an XML standard that extends basic linking capabilities by enabling rich, multidirectional, and metadata-enhanced hyperlinks between resources.
  • F. None of above. chosen

Provenance (5 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85c9cff48190900d234a7569cd5d completed March 20, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf18c8db388190a31f55854e7370fc completed March 21, 2026, 10:16 p.m.
NEDg Description generation batch_69bf19c8273081908a5138e9af921ec7 completed March 21, 2026, 10:20 p.m.
NED2 Entity disambiguation (via description) batch_69bf1a3049648190b5040e587671610a completed March 21, 2026, 10:22 p.m.
Created at: March 20, 2026, 2 p.m.