Triple

T2533999
Position Surface form Disambiguated ID Type / Status
Subject Atlantic–Congo languages E56225 entity
Predicate includesLanguage P2177 FINISHED
Object Ganda E275005 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: Ganda | Statement: [Atlantic–Congo languages, includesLanguage, Ganda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ganda
Context triple: [Atlantic–Congo languages, includesLanguage, Ganda]
  • A. Ganda chosen
    Ganda is a Bantu language spoken primarily in Uganda, where it serves as a major lingua franca and the language of the Baganda people.
  • B. Guna
    Guna is a city in the central Indian state of Madhya Pradesh known as an important regional administrative and commercial center.
  • C. Undun
    Undun is a concept album by hip hop band The Roots that narrates the rise and fall of a fictional young man through introspective, jazz-influenced production and storytelling.
  • D. Gan
    Gan is a common abbreviated name and historical-cultural designation for Jiangxi Province in southeastern China.
  • E. Beni
    Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
  • 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_69ab4a49b6508190bc467fbef4bac334 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd27afe7c8190984e10d3f3d5586b completed March 7, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69af655441b0819088b86498520ee3b4 completed March 10, 2026, 12:27 a.m.
Created at: March 6, 2026, 9:47 p.m.