Triple

T10330325
Position Surface form Disambiguated ID Type / Status
Subject TEI E242855 entity
Predicate hasComponent P35 FINISHED
Object TEI Guidelines E242855 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: TEI Guidelines | Statement: [TEI, hasComponent, TEI Guidelines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TEI Guidelines
Context triple: [TEI, hasComponent, TEI Guidelines]
  • A. TEI chosen
    TEI (Text Encoding Initiative) is a widely used standard for encoding and representing texts in digital form, especially in the humanities, using XML-based guidelines.
  • B. JATS
    JATS (Journal Article Tag Suite) is an XML-based standard for tagging and exchanging scholarly journal content, widely used for structuring and archiving scientific articles.
  • C. DocBook
    DocBook is a semantic markup language, originally based on SGML and now commonly used in XML form, designed for authoring and publishing technical documentation and books in a platform-independent way.
  • D. SGML
    SGML (Standard Generalized Markup Language) is a standardized metalanguage for defining markup languages used to structure and describe the content of electronic documents.
  • E. DITA
    DITA (Darwin Information Typing Architecture) is an XML-based standard for authoring, structuring, and publishing modular technical documentation.
  • 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d7fb77348190ac8ff887f6f03450 completed April 7, 2026, 10:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71dbc7df48190b8a11a92f946fd30 completed April 9, 2026, 3:32 a.m.
Created at: April 6, 2026, 11:52 a.m.