Triple

T25310545
Position Surface form Disambiguated ID Type / Status
Subject pengő E634595 entity
Predicate hadBanknotes P158374 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: [pengő, hadBanknotes, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hadBanknotes
Context triple: [pengő, hadBanknotes, yes]
  • A. hasBanknotes
    Indicates that an entity possesses or contains one or more banknotes.
  • B. hadDistinctBanknotes
    Indicates that the subject possessed or used banknotes that were different in denomination, design, or identifying features from those of the other entity in the relation.
  • C. issuesBanknotes
    Indicates that an entity (typically a central bank or monetary authority) produces and puts banknotes into official circulation as legal tender.
  • D. frequentlyUsedBanknotes
    Indicates that the referenced banknotes are commonly or regularly used in transactions within a given context or system.
  • E. typeOfBanknotes
    Indicates a relationship where one entity specifies the kind or category of banknotes associated with another entity.
  • F. None of above. chosen

Provenance (4 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_69e75a972c6481909bc11710e8d30a6c completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f4939e84dc8190bef761d9bfee08a6 completed May 1, 2026, 11:50 a.m.
PD Predicate disambiguation batch_69f45d06d0388190b36ecde92013624a completed May 1, 2026, 7:57 a.m.
PDg Predicate description generation batch_69f465699c9c8190ac7b4b32b782550c completed May 1, 2026, 8:33 a.m.
Created at: April 21, 2026, 1:26 p.m.