Triple

T18563548
Position Surface form Disambiguated ID Type / Status
Subject Unicode Technical Reports E453704 entity
Predicate documentFormat P130 FINISHED
Object PDF NE NERFINISHED

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: PDF | Statement: [Unicode Technical Reports, documentFormat, PDF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PDF
Context triple: [Unicode Technical Reports, documentFormat, PDF]
  • A. PDF/E
    PDF/E is an ISO-standardized subset of the PDF format designed specifically for reliable creation, exchange, and archiving of engineering and technical documents, such as CAD and geospatial data.
  • B. PDF/A
    PDF/A is an ISO-standardized version of the PDF format designed specifically for long-term archiving and reliable reproduction of electronic documents.
  • C. Pades
    Pades is a village in northwestern Greece located in the mountainous region near Mount Smolikas.
  • D. Portable Document Format chosen
    Portable Document Format (PDF) is a widely used file format designed for reliably presenting and exchanging documents independent of software, hardware, or operating systems.
  • E. PDF/VT
    PDF/VT is an ISO-standardized subset of the PDF format designed specifically for variable and transactional printing, enabling efficient, high-volume personalized document production.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38974308190a9174430ef256b73 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53afc57448190abd90167d7e12a18 completed April 19, 2026, 8:28 p.m.
Created at: April 10, 2026, 11:42 a.m.