Triple

T11681026
Position Surface form Disambiguated ID Type / Status
Subject Bhaca E277613 entity
Predicate hasLanguageVariety P5595 FINISHED
Object Bhaca language E915106 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: Bhaca language | Statement: [Bhaca, hasLanguageVariety, Bhaca language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bhaca language
Context triple: [Bhaca, hasLanguageVariety, Bhaca language]
  • A. Bhaca language chosen
    The Bhaca language is a Bantu language of South Africa spoken primarily by the Bhaca people in the Eastern Cape and surrounding regions.
  • B. Baka language
    The Baka language is a Central African language spoken primarily by the Baka Pygmy communities in parts of Cameroon, Gabon, and the Republic of the Congo.
  • C. Bwaka language
    The Bwaka language is a Central Sudanic language of the Gbaya group spoken by the Bwaka people in parts of Central Africa.
  • D. Aka-Bea language
    The Aka-Bea language is an extinct indigenous tongue once spoken by the Great Andamanese Aka-Bea people of the Andaman Islands in the Bay of Bengal.
  • E. Bambam language
    The Bambam language is an Austronesian language spoken in parts of South Sulawesi, Indonesia, known for its place within the region’s diverse indigenous linguistic landscape.
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a461b0908190bef4e1c6777affcf completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef83098e2c819081c22462372f64b4 completed April 27, 2026, 3:38 p.m.
Created at: April 8, 2026, 9:40 p.m.