Triple

T285366
Position Surface form Disambiguated ID Type / Status
Subject Latin E5875 entity
Predicate influenced P9 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: [Latin, influenced, Catalan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catalan
Context triple: [Latin, influenced, 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. 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.
  • C. 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.
  • D. Niçard Occitan
    Niçard Occitan is a Romance variety of the Occitan language traditionally spoken in and around the city of Nice in southeastern France.
  • E. Catalonia
    Catalonia is an autonomous community in northeastern Spain with a distinct Catalan language and culture, a strong regional identity, and Barcelona as its capital.
  • 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_69a25946a7ac8190a78871c210213272 completed Feb. 28, 2026, 2:56 a.m.
NER Named-entity recognition batch_69a25e2c73a48190b549b688254e5fee completed Feb. 28, 2026, 3:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69a39d078ad88190b4fce535c8ea9a80 completed March 1, 2026, 1:57 a.m.
Created at: Feb. 28, 2026, 3:02 a.m.