Triple

T380463
Position Surface form Disambiguated ID Type / Status
Subject SGML E8666 entity
Predicate abbreviation P43 FINISHED
Object SGML E8666 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: SGML | Statement: [SGML, abbreviation, SGML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SGML
Context triple: [SGML, abbreviation, SGML]
  • A. SGML chosen
    SGML (Standard Generalized Markup Language) is a standardized metalanguage for defining markup languages used to structure and describe the content of electronic documents.
  • B. DSSSL
    DSSSL (Document Style Semantics and Specification Language) is an ISO standard language used to define stylesheets and transformations for SGML documents, particularly in technical publishing.
  • C. XML
    XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
  • D. XHTML
    XHTML is a reformulation of HTML as an XML-based markup language designed to create structured, standards-compliant web pages.
  • E. RELAX NG
    RELAX NG is a schema language used to define and validate the structure and content of XML documents in a concise and flexible way.
  • 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_69a2e7f47dd08190a4e294ccbbe46cd4 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec2c95088190a603bb1ee076ebd6 completed Feb. 28, 2026, 1:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3fe92911881908ee7f88d5c628ec9 completed March 1, 2026, 8:53 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.