Triple

T220500
Position Surface form Disambiguated ID Type / Status
Subject West African languages E4201 entity
Predicate influenced P9 FINISHED
Object Sranan Tongo E4255 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: Sranan Tongo | Statement: [West African languages, influenced, Sranan Tongo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sranan Tongo
Context triple: [West African languages, influenced, Sranan Tongo]
  • A. Sranan Tongo chosen
    Sranan Tongo is an English- and Dutch-influenced creole language originating in Suriname, widely used as a lingua franca among its diverse ethnic communities.
  • B. Shona
    Shona is a major Bantu language of Zimbabwe, widely spoken by the Shona people and used in education, media, and government.
  • C. Solomon Islands Pijin
    Solomon Islands Pijin is an English-based creole language widely used as a lingua franca across the Solomon Islands.
  • D. Tshivenda
    Tshivenda is a Bantu language spoken primarily by the Venda people in northern South Africa and neighboring regions.
  • E. Waray language
    Waray is an Austronesian language spoken primarily in the Eastern Visayas region of the Philippines, particularly on Samar and nearby islands.
  • 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_69a2573508588190b522c2476d91acfe completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c6d0fa08190810139b14f4851bc completed Feb. 28, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69a358799c04819099e9795809236b31 completed Feb. 28, 2026, 9:04 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.