Triple

T3085487
Position Surface form Disambiguated ID Type / Status
Subject Buglere language E64360 entity
Predicate hasAlternativeName P39 FINISHED
Object Buglé E160527 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: Buglé | Statement: [Buglere language, hasAlternativeName, Buglé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buglé
Context triple: [Buglere language, hasAlternativeName, Buglé]
  • A. Buglé chosen
    The Buglé are an Indigenous people of western Panama, closely related to the Ngäbe and known for their distinct language, traditional subsistence farming, and communal social organization.
  • B. Catroux
    Catroux is a French surname most notably borne by Georges Catroux, a prominent French general and diplomat of the 20th century.
  • C. Bellhorn
    Bellhorn is the surname of former Major League Baseball infielder Mark Bellhorn, known for his key role with the Boston Red Sox during their 2004 championship season.
  • D. Galich
    Galich is a historic Russian town in Kostroma Oblast known for its medieval origins and its location on the shores of Lake Galichskoye.
  • E. Nantz
    Nantz is the surname of Jim Nantz, a prominent American sportscaster best known for his long-running work with CBS Sports covering events like the NFL, NCAA basketball, and The Masters.
  • 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_69ad857bb4c88190a4cf27893fcabed8 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada1eac5548190bee60ea8262c65a8 completed March 8, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1f89e6f5c8190993794e2c9977ee6 completed March 11, 2026, 11:19 p.m.
Created at: March 8, 2026, 3:03 p.m.