Triple

T6408787
Position Surface form Disambiguated ID Type / Status
Subject DTD E127654 entity
Predicate appliesTo P1129 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: [DTD, appliesTo, SGML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SGML
Context triple: [DTD, appliesTo, 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. SAX
    SAX (Simple API for XML) is an event-driven, streaming XML parsing interface commonly used for efficiently processing large XML documents in a forward-only manner.
  • D. DTD
    DTD (Document Type Definition) is an XML schema language used to define the legal structure, elements, and attributes of an XML document.
  • E. DTD
    DTD is the abbreviated name for the Division of Training and Development, an organizational unit focused on designing and delivering training and professional development programs.
  • 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_69c0083723d88190b1e37b19df162c08 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c068cdf25881908d42a5d979637ad6 completed March 22, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c638b38c888190aa2433173db64c90 completed March 27, 2026, 7:58 a.m.
Created at: March 22, 2026, 4:41 p.m.