Triple

T2103053
Position Surface form Disambiguated ID Type / Status
Subject World War I poetry E37132 entity
Predicate hasLanguage P15 FINISHED
Object Catalan E5109 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: Catalan | Statement: [World War I poetry, hasLanguage, Catalan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catalan
Context triple: [World War I poetry, hasLanguage, Catalan]
  • A. Catalan chosen
    Catalan is a Romance language spoken primarily in Catalonia, Valencia, the Balearic Islands, and parts of eastern Spain and southern France.
  • B. Catalan Wikinews
    Catalan Wikinews is the Catalan-language edition of the Wikinews project, offering collaboratively written, free-content news articles.
  • C. Aragonese language
    The Aragonese language is a minority Romance language spoken primarily in the Aragon region of northeastern Spain, closely related to Spanish and Catalan.
  • D. Occitan
    Occitan is a Romance language historically spoken in southern France and neighboring regions, known for its rich medieval literary tradition and close relation to Catalan.
  • E. Pré-Catelan
    Pré-Catelan is a landscaped garden and leisure area within Paris’s Bois de Boulogne, known for its lawns, trees, and outdoor cultural events.
  • 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_69a8861828948190924aa30c08806b3a completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abbabe1e9081908ea66c5406e2f1d9 completed March 7, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae3068189c81909cf76fd1fc2a0fe6 completed March 9, 2026, 2:28 a.m.
Created at: March 4, 2026, 7:43 p.m.