Triple

T4893334
Position Surface form Disambiguated ID Type / Status
Subject VOA Africa E109614 entity
Predicate languageOfBroadcast P3314 FINISHED
Object Wolof E28117 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: Wolof | Statement: [VOA Africa, languageOfBroadcast, Wolof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wolof
Context triple: [VOA Africa, languageOfBroadcast, Wolof]
  • A. Wolof chosen
    Wolof is a major Niger-Congo language spoken primarily in Senegal, The Gambia, and Mauritania, serving as a key lingua franca in the region.
  • B. Casamance Creole
    Casamance Creole is a Portuguese-based creole language spoken primarily in the Casamance region of Senegal, influenced by local West African languages.
  • C. Dioula
    Dioula is a Mande language of West Africa, widely used as a trade and lingua franca language in countries like Burkina Faso, Côte d’Ivoire, and Mali.
  • D. Tamasheq
    Tamasheq is a Berber language spoken by the Tuareg people of the central Sahara region.
  • E. Bambara
    Bambara is a major Mande language widely spoken in Mali and neighboring West African countries, serving as a key lingua franca in the region.
  • 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_69bd4410bbf88190aad50d2451c863d6 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e257b0481909fd60eb29351b6d8 completed March 20, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fc2f00881908cae1e68df2019e3 completed March 21, 2026, 10:15 a.m.
Created at: March 20, 2026, 1:28 p.m.