Triple

T14864827
Position Surface form Disambiguated ID Type / Status
Subject National Széchényi Library E349589 entity
Predicate hasLegalDepositSystem P13082 FINISHED
Object yes LITERAL 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: yes | Statement: [National Széchényi Library, hasLegalDepositSystem, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLegalDepositSystem
Context triple: [National Széchényi Library, hasLegalDepositSystem, yes]
  • A. hasLegalDeposit
    Indicates that an entity is required to deposit copies of its published material with a designated legal deposit institution or repository.
  • B. hasLegalDepositRightFor
    Indicates that an entity holds the legal right to receive, collect, or claim deposited materials (such as publications or documents) from another entity under legal deposit regulations.
  • C. hasLegalDepositLibrariesNetwork chosen
    Indicates that an entity is associated with or participates in a network of libraries designated for legal deposit of published materials.
  • D. hasDigitalLibrary
    Indicates that an entity maintains or provides access to a collection of digital resources or publications.
  • E. usesDRM
    Indicates that one entity applies digital rights management (DRM) controls or technologies to another entity (such as content, software, or media).
  • F. None of above.

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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded574d0ec8190a6afed672ba6c2f9 completed April 15, 2026, 12:01 a.m.
PD Predicate disambiguation batch_69de8c1798c08190b433e9ad21e41a42 completed April 14, 2026, 6:48 p.m.
Created at: April 10, 2026, 1:54 a.m.