Triple

T11988875
Position Surface form Disambiguated ID Type / Status
Subject Catalan Countries E285352 entity
Predicate includes P1393 FINISHED
Object El Carxe E909504 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: El Carxe | Statement: [Catalan Countries, includes, El Carxe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: El Carxe
Context triple: [Catalan Countries, includes, El Carxe]
  • A. El Carxe chosen
    El Carxe is a small Catalan-speaking enclave in the Region of Murcia, Spain, known for its unique linguistic and cultural identity.
  • B. Carso
    Carso is a limestone plateau region in northeastern Italy and southwestern Slovenia, known for its distinctive karst landscapes, caves, and sinkholes.
  • C. Vacarisses
    Vacarisses is a small municipality in Catalonia, Spain, known for its rural character and location within the comarca of Vallès Occidental.
  • D. La Coche
    La Coche is one of the small islands in the Les Saintes archipelago in the Caribbean, known for its rugged coastline and surrounding marine life.
  • E. Calvero
    Calvero is the aging, once-famous clown portrayed by Charlie Chaplin in the 1952 film "Limelight," struggling with obscurity and seeking redemption through helping a young dancer.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903ae28708190a826bad1624343eb completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f472492ebc8190b064e691bb70e356 completed May 1, 2026, 9:28 a.m.
Created at: April 8, 2026, 9:46 p.m.