Triple

T118477
Position Surface form Disambiguated ID Type / Status
Subject Italian lira E2393 entity
Predicate lastSeriesBanknotesFeatured P7633 FINISHED
Object Maria Montessori (1000 lire) 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: Maria Montessori (1000 lire) | Statement: [Italian lira, lastSeriesBanknotesFeatured, Maria Montessori (1000 lire)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: lastSeriesBanknotesFeatured
Context triple: [Italian lira, lastSeriesBanknotesFeatured, Maria Montessori (1000 lire)]
  • A. banknoteDenomination
    Indicates the specific face value assigned to a banknote in a given currency.
  • B. languageOnBanknotes
    Indicates the language that is printed or used on a country's banknotes.
  • C. centralBank
    Indicates that an entity functions as the primary monetary authority responsible for issuing currency and implementing monetary policy for a specific jurisdiction.
  • D. isLegalTenderFor
    Indicates that a particular currency or form of money is officially recognized by a governing authority as valid payment for debts and financial transactions within a specified jurisdiction.
  • E. notableEdition
    Indicates that a particular edition or version of a work is especially significant or noteworthy in relation to that work.
  • 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_69a2506c5428819085c28a8884790e29 completed Feb. 28, 2026, 2:18 a.m.
NER Named-entity recognition batch_69a258e0b11c8190b7b5cf3c354c47ce completed Feb. 28, 2026, 2:54 a.m.
PD Predicate disambiguation batch_69a25646d5088190a057989c32da3a90 completed Feb. 28, 2026, 2:43 a.m.
PDg Predicate description generation batch_69a258de46888190835db2b21a093eaa completed Feb. 28, 2026, 2:54 a.m.
Created at: Feb. 28, 2026, 2:24 a.m.