Triple

T6015755
Position Surface form Disambiguated ID Type / Status
Subject André Campra E133945 entity
Predicate familyName P18 FINISHED
Object Campra E372383 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: Campra | Statement: [André Campra, familyName, Campra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Campra
Context triple: [André Campra, familyName, Campra]
  • A. Mascarille
    Mascarille is a comic valet character in Molière’s play *Les Précieuses ridicules*, known for his affected manners and satirical portrayal of social pretension.
  • B. Guamo
    Guamo is a municipality and agricultural town in central Colombia’s Tolima Department, known for its warm climate and regional farming economy.
  • C. Filabusi
    Filabusi is a small mining and agricultural town in southwestern Zimbabwe that serves as a local commercial and administrative center.
  • D. Echenique chosen
    Echenique is a Spanish-language surname of Basque origin borne by various notable figures in politics, arts, and public life across the Spanish-speaking world.
  • E. Coma Pedrosa
    Coma Pedrosa is the tallest mountain in Andorra, known for its rugged alpine terrain and popular hiking routes.
  • 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_69c0087361a48190905c6b55969852b8 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04f80ec108190ae9711727debb061 completed March 22, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c108ade3948190994fbaa2a5539216 completed March 23, 2026, 9:32 a.m.
Created at: March 22, 2026, 4:06 p.m.