Triple

T1332442
Position Surface form Disambiguated ID Type / Status
Subject Sranan E28672 entity
Predicate substrateLanguage P11299 FINISHED
Object Kikongo language E57354 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: Kikongo language | Statement: [Sranan, substrateLanguage, Kikongo language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kikongo language
Context triple: [Sranan, substrateLanguage, Kikongo language]
  • A. Kikongo chosen
    Kikongo is a Bantu language widely spoken in Central Africa, particularly in the western regions of the Democratic Republic of the Congo and neighboring countries.
  • B. Lingala
    Lingala is a Bantu language widely spoken as a lingua franca in the Democratic Republic of the Congo and the Republic of the Congo, especially in urban centers and along the Congo River.
  • C. Kimbundu
    Kimbundu is a major Bantu language spoken primarily in northwestern Angola, especially around the capital Luanda, by the Ambundu people.
  • D. Kirundi
    Kirundi is a Bantu language primarily spoken in Burundi and neighboring regions of East Africa.
  • E. Konjo language
    The Konjo language is an Austronesian language spoken by the Konjo people of South Sulawesi, Indonesia, known for its distinct coastal and highland dialects.
  • 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_69a498561a508190a3e1bc137c2b866a completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1e7f1388190a6e4eb65a7997380 completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbf383b24819092acd076130ca5c0 completed March 8, 2026, 12:13 a.m.
Created at: March 1, 2026, 7:55 p.m.