Triple

T17150496
Position Surface form Disambiguated ID Type / Status
Subject Sub-sindic General E416206 entity
Predicate languageOfName 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: [Sub-sindic General, languageOfName, Catalan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catalan
Context triple: [Sub-sindic General, languageOfName, 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. Catalão
    Catalão is a municipality in the southeastern part of the Brazilian state of Goiás, known for its agriculture, mining activities, and growing industrial sector.
  • C. Catalan Wikipedia
    Catalan Wikipedia is the Catalan-language edition of the free, collaboratively edited online encyclopedia Wikipedia.
  • D. Valencian Spanish
    Valencian Spanish is a regional variety of Spanish spoken in the Valencian Community in eastern Spain, characterized by influences from both standard Spanish and the local Valencian (Catalan) language.
  • E. Catalan Wikisource
    Catalan Wikisource is the Catalan-language edition of Wikisource, a free online digital library of public domain and freely licensed texts.
  • 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f4067470819084aa233c4c4a6d4f completed April 18, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01415b1d7c81908d000b0362042687 completed May 11, 2026, 2:39 a.m.
Created at: April 10, 2026, 5:36 a.m.